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Self-reported sleep duration and cognitive functioning in a general population

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This study investigated the relationship between self-reported sleep factors (sleep duration, insomnia, use of sleeping medicine, probable sleep apnoea and feelings of fatigue and tiredness) with cognitive functioning in 5177 people aged 30 years or older from a cross-sectional representative sample of the adult population in Finland (The Finnish Health 2000 Survey). Previous studies have indicated a U-shaped association between increased health risks and sleep duration; we hypothesized a U-shaped association between sleep duration and cognitive functioning. Objective cognitive functioning was assessed with tasks derived from the Consortium to Establish a Registry for Alzheimer's Disease test battery (verbal fluency, encoding and retaining verbal material). Subjective cognitive functioning and sleep-related factors were assessed with questionnaires. Health status was assessed during a health interview. Depressive and alcohol use disorders were assessed with the Composite International Diagnostic Interview. Medication was recorded during the health examination. Short and long sleep duration, tiredness and fatigue were found to be associated with both objectively assessed and self-reported decreased cognitive functioning. The association was stronger between sleep factors and subjective cognitive function than with objective cognitive tests. These data suggest that self-reported habitual short and long sleep duration reflect both realization of homeostatic sleep need and symptom formation in the context of the individual's health status.
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doi: 10.1111/j.1365-2869.2009.00765.x
Self-reported sleep duration and cognitive functioning in the
general population
ERKKI KRONHOLM
1
, MIKAEL SALLINEN
2,3
, TIMO SUUTAMA
4
,
RAIMO SULKAVA
5
,PERTTIERA
6
and TIMO PARTONEN
7
1
Department of Chronic Disease Prevention, National Institute for Health and Welfare, Turku,
2
Brain Work Research Center, Finnish Institute of
Occupational Health, Helsinki,
3
Agora Center and
4
Department of Psychology, University of Jyva
¨skyla
¨, Jyva
¨skyla
¨,
5
Department of Geriatrics,
School of Public Health and Clinical Nutrition, University of Kuopio, Kuopio,
6
Department of Health Sciences, Finnish Centre for
Interdisciplinary Gerontology, University of Jyva
¨skyla
¨, Jyva
¨skyla
¨and
7
Department of Mental Health and Substance Abuse Services Unit,
National Institute for Health and Welfare, Helsinki, Finland
Accepted in revised form 22 February 2009; received 26 November 2008
SUMMARY This study investigated the relationship between self-reported sleep factors (sleep
duration, insomnia, use of sleeping medicine, probable sleep apnoea and feelings of
fatigue and tiredness) with cognitive functioning in 5177 people aged 30 years or older
from a cross-sectional representative sample of the adult population in Finland (The
Finnish Health 2000 Survey). Previous studies have indicated a U-shaped association
between increased health risks and sleep duration; we hypothesized a U-shaped
association between sleep duration and cognitive functioning. Objective cognitive
functioning was assessed with tasks derived from the Consortium to Establish a
Registry for AlzheimerÕs Disease test battery (verbal fluency, encoding and retaining
verbal material). Subjective cognitive functioning and sleep-related factors were
assessed with questionnaires. Health status was assessed during a health interview.
Depressive and alcohol use disorders were assessed with the Composite International
Diagnostic Interview. Medication was recorded during the health examination. Short
and long sleep duration, tiredness and fatigue were found to be associated with both
objectively assessed and self-reported decreased cognitive functioning. The association
was stronger between sleep factors and subjective cognitive function than with objective
cognitive tests. These data suggest that self-reported habitual short and long sleep
duration reflect both realization of homeostatic sleep need and symptom formation in
the context of the individualÕs health status.
keywords cognitive functioning, general population, sleep duration
INTRODUCTION
A number of epidemiological studies have revealed an asso-
ciation of self-reported sleep duration with morbidity and
mortality (Ayas et al., 2003; Hublin et al., 2007; Yaggi et al.,
2006) [for reviews, see Grandner and Drummond (2007) and
Youngstedt and Kripke (2004)]. The commonly reported
finding is that both short and long habitual sleep durations
are associated with impaired health and increased mortality.
Another important but less extensively investigated question is
whether habitual sleep duration is associated with variations in
cognitive functioning.
The impact of experimentally manipulated sleep duration on
cognitive functions has been examined repeatedly. Numerous
studies have demonstrated that both acute total and cumula-
tive partial sleep loss lead to deteriorations in a wide range of
cognitive functions such as sustained attention, executive
functions and memory functions [for reviews, see Banks and
Dinges (2007) and Jones and Harrison (2001)]. These studies
suggest that short sleepers in the general population may show
Correspondence: Erkki Kronholm, Department of Chronic Disease
Prevention, National Institute for Health and Welfare, Turku,
Finland. Tel.: +358 2 331 6718; fax: +358 2 331 6720;
e-mail: erkki.kronholm@thl.fi
J. Sleep Res. (2009) 18, 436–446 Sleep duration and cognitive function
436 2009 European Sleep Research Society
inferior cognitive performance when compared with 7–8 h
sleepers. Experimental studies on sleep extension have shown
primarily that only marginal improvements in daytime sleep-
iness and psychomotor performance can be seen following
extended sleep: in some studies, detrimental effects have been
reported [for a review, see Ferrara and De Gennaro (2001)].
However, substantial improvements have also been reported
(Kamdar et al., 2004). In light of data from sleep restriction
and extension experiments, long sleepers in the general
population could be assumed to perform similarly to or even
better than mid-range sleepers. However, because self-reported
sleep duration is not an accurate measure of physiological
sleep amount (Jean-Louis et al., 2000; Kripke, 2004) the results
from experimental studies may not be applicable to habitual
self-reported sleep duration in the general population.
The few existing epidemiological studies have reported
contradictory relationships between self-reported habitual
sleep duration and cognitive functioning. In a sample of
1269 community-dwelling older people (age 60 years), self-
reported short sleep (£6 h) and daytime napping (1 h) were
associated with impaired self-reported cognitive functioning
(Ohayon and Vecchierini, 2005). Long sleep (9.5 h), on the
other hand, showed no relationship to the level of self-reported
cognitive functioning. The most straightforward association
was found between daytime sleepiness and self-reported
cognitive impairment. Another study (Schmutte et al., 2007)
found a relationship between self-reported sleep duration and
objectively measured cognitive performance in non-demented
community-dwelling older adults (n=375; mean age,
79.6 years). The evidence was strongest for the relationship
between long sleep (>9 h) and impaired performance on a
verbal short-term memory test. Further evidence for the role of
habitually insufficient sleep in cognitive functioning comes
from a study among shift workers (n=3237) (Rouch et al.,
2005). In comparison with non-shift workers, male shift
workers (but not females) showed slower cognitive processing.
In addition, those who had stopped working shifts more than
4 years ago demonstrated no cognitive impairments. These
results imply that habitually insufficient sleep due to a
disrupted circadian rhythm leads to the deterioration of
cognitive functioning, at least in men.
For this study, our aim was to elucidate further the
relationship between self-reported habitual sleep duration
and cognitive functioning. In contrast to the above-mentioned
epidemiological studies, we used a representative sample of the
general adult population as our target group in order to obtain
a general picture of the relationship in most adults. To
examine the participantsÕcognitive functioning, we employed
both performance tests and self-assessment. In addition, we
explored a variety of pertinent factors that are likely to
influence the relationship between sleep duration and cognitive
performance, such as insomnia symptoms (Kronholm et al.,
2006; Schmutte et al., 2007), sleep-disordered breathing (Beebe
and Gozal, 2002; Cohen-Zion et al., 2001, 2004; Engleman and
Joffe, 1999; Telakivi et al., 1988), depression (Paradiso et al.,
1997), alcohol consumption (Dao-Castellana et al., 1998),
drug use (Silva et al., 2003) and certain sociodemographic
factors.
METHODS
This study was based on the Health 2000 Survey, a compre-
hensive nationwide interview and health examination survey
carried out in Finland in 2000–2001 (Aromaa and Koskinen,
2004). The implementation, target population, sampling
design, samples and methods of the survey are described in
detail at http://www.ktl.fi/health2000 [see also Kronholm et al.
(2006)]. In brief, from a sample comprised of 8028 people aged
30 years or older, 6986 people (87%) were met by the
interviewers at the participantsÕhome or in an institution.
During the interviews, the respondents were given an
information leaflet and an informed consent form to sign
and return. During the health interview, the participants were
also given questionnaire 1, which they were asked to complete
and bring along to the subsequent comprehensive health
examination, which took place a few weeks afterwards in local
health centres. If the invited participants did not attend, an
abridged examination was conducted at home. The question-
naire was returned by 6460 people (80% of the original
sample). During the health examination, the participants were
given questionnaire 3 to be returned by mail. Questionnaire 3
was completed by 6269 individuals (78% of the sample); for all
questionnaires, see http://www.ktl.fi/health2000.
For the analyses of this study, 21 participants who were
suspected to have dementia based on abbreviated Mini-Mental
Sate Examination (not described here) performed at the health
examination, and six participants who used medicine for
AlzheimerÕs disease, were excluded. Thus, the final analysis
sample (participants with complete information across cogni-
tive performance variables) comprised 5171 participants (2333
men and 2838 women). In different statistical models missing
information across variables caused slight variation in the
number of participants. The study was approved by the Ethics
Committee for Epidemiology and Public Health in the
Hospital District of Helsinki and Uusimaa in Finland.
MEASURES
Cognitive functions
Objective cognitive tests
Verbal fluency (speech production) and encoding and retaining
verbal material were assessed by means of selected tasks
deriving from the Consortium to Establish a Registry for
AlzheimerÕs Disease (CERAD) test battery which was devel-
oped originally for the purpose of assessing early phases of
dementia and memory disturbances (Aromaa and Koskinen,
2004; Morris et al., 1989). The selected CERAD tests were
carried out as part of the health examination of all attendees
aged 30 years or over. To assess verbal fluency, participants
were requested to list as many animals as possible
within 1 min. Verbal fluency has been shown to be prefrontal
Sleep duration and cognitive functioning 437
2009 European Sleep Research Society, J. Sleep Res.,18, 436–446
cortex-focused and sensitive to sleep deprivation (Harrison
and Horne, 1997, 1998; Herrmann et al., 2003). The outcome
was reported in terms of words per minute (Jones and
Harrison, 2001).
Memory function was examined by means of three trials
testing the learning of a list of 10 words by reading the list
aloud three times. After each trial, the participant was asked to
repeat the words he or she remembered. The outcome variable
was the sum of scores across all three trials. (If a participant
learned all 10 words successfully in the first or second trial, the
following trial(s) was were scored 10 points without an actual
attempt). The outcome variable is herein referred to as the
Ôlearning effectÕ. Delayed recall was assessed by asking the
participants to repeat the list after 5 min. The recall rate (the
percentage of remembered words from the number of origi-
nally learnt words) was used as an outcome variable in this test
(Aromaa and Koskinen, 2004).
Self-assessed cognitive functioning
During the home interviews self-reported memory function
was assessed by means of the following question: ÔHow would
you estimate your present memory? Is your memory: very
good; good; satisfactory; poor; very poor?Õ(for subsequent
analyses, the variables itemized were very good good
=ÔgoodÕ; satisfactory = ÔsatisfactoryÕ; and poor very
poor = ÔpoorÕ).
Sleep-related measures
Sleep duration groups
Self-reported 24-h sleep duration was used for the classification
of the participants into four sleep duration groups. The
participants were asked (questionnaire 3): ÔHow many hours
do you sleep in 24 h?Õ(no time-frame was referenced for this
question). The responses were recorded in whole numbers. For
the purposes of this study, the participants were divided into
four groups according to their sleep duration. The classifica-
tion was based on previous reports of the associations between
self-reported sleep duration and mortality and morbidity [for
references, see Bliwise and Young (2007); Grandner and
Drummond (2007) and Youngstedt and Kripke (2004). The
groups were labelled as Ôshort sleepersÕ(6 h or less), Ô7-h
sleepersÕ(7 h), Ô8-h sleepersÕ(8 h) and Ôlong sleepersÕ(9 h or
more).
Insomnia and its daytime consequences
To assess insomnia and its consequences, the following
questions were asked: ÔHave you had any of the following
usual symptoms and troubles within the last month (30 days):
(i) sleeping disorders or insomnia and (ii) fatigue and tiredness?
(questionnaire 1). Exceptional tiredness was assessed by the
question: ÔAre you usually more tired during the daytime than
other people of your age?Õ(questionnaire 3). Benzodiazepines
are the most commonly used hypnotics in the treatment of
insomnia in Finland (National Agency for Medicines and
Social Insurance Institution, 2006). It has been reported that
benzodiazepine-based hypnotic drugs affect the consolidation
of memory during sleep (Silva et al., 2003). Therefore, use of
hypnotics [Anatomical Therapeutic Chemical (ATC) classifi-
cation: code N05C] was included in the sleep-related factors
applied in the models predicting cognitive function.
Probable sleep apnoea
The following questions (all from questionnaire 3) and logic
were used in order to determine the occurrence of probable
sleep apnoea. If a participant answered ÔnoÕto the question:
ÔDo you snore when sleeping? (ask others, if you are not sure)Õ,
sleep apnoea was considered to be unlikely. If the answer was
ÔyesÕ, then the following additional questions were asked: (i)
ÔHow often do you snore?Õ; (ii) ÔHow does your snoring sound?Õ
(ask others, if needed); and (iii) ÔHave you noticed (or have
others noticed) respiratory pauses when you sleep?Õ. Sleep
apnoea was considered quite probable, if snoring was frequent
(at least during 3–5 nights weekly) and either or both of the
following items was positive: (i) snoring is loud and irregular
with occasional respiratory pauses and or stertorous breath-
ing and (ii) respiratory pauses with a frequency of at least 1–2
nights weekly. In all other cases, sleep apnoea was considered
unlikely.
Health indicators
During the health interview the participants were asked to
report all illnesses diagnosed by a doctor. The reported
diseases and symptoms were classified into 91 groups. From
these, 21 most prevalent (range 11.3–0.9%) groups were
considered as possibly modulating cognitive performance. A
multivariable model was performed with all 21 disease groups
as explanatory variables and word fluency as the dependent
variable. The model revealed that 11 illness variables were
independent statistical predictors of cognitive performance.
These 11 variables were then selected to be used as health
indicators possibly modulating cognitive performance. The
considered illnesses and their prevalence in the study sample
were hypertension (11.3%), musculoskeletal diseases (9.1%),
arthrosis (7.1%), disease of the circulatory system (4.5%),
coronary artery disease (3.8%), diabetes (3.6%), allergic
reaction (2.5%), symptoms related to vascular diseases
(1.9%), neurological diseases (1.8%), cerebrovascular disease
(1.2%) and chronic respiratory system inflammation (0.9%).
In addition, during the comprehensive health examination,
the Composite International Diagnostic Interview (CIDI) to
identify mental disorders was performed. The computerized
version of the CIDI uses operationalized criteria for DSM-IV
diagnoses and allows the estimation of DSM-IV diagnoses for
major mental disorders [for details, see Pirkola et al. (2005)].
The 12-month prevalence rates of major depressive episodes
and disorder as well as alcohol dependence were used in this
438 E. Kronholm et al.
2009 European Sleep Research Society, J. Sleep Res.,18, 436–446
study as health indicators possibly modulating cognitive
performance. Further, the use of neuroleptics (ATC code
N05A) and antidepressants (ATC code N06A) were considered
in this study as health indicators possibly modulating cognitive
performance.
Sociodemographic factors
Age, gender and education were included into the variables
possibly modulating cognitive performance. The itemized
variable ÔeducationÕcombined the whole educational history
of a participant (the basic education and vocational university
education). More specifically, participants without matricula-
tion examination who had no vocational education or only
training or technical certificate for courses completed were
classified into Ôthe basic educational groupÕ(variable educa-
tion = 1); participants without matriculation examination
who had an apprenticeship contract, completed vocational
school or who had a technical college qualification were
classified into Ôthe secondary educational groupÕ(variable
education = 2); participants who, after basic education, also
had a university degree or special higher vocational qualifica-
tion were classified into Ôthe higher educational groupÕ(vari-
able education = 3).
Data analyses and statistics
Statistical analyses were completed using the Statistical Anal-
ysis System (SAS) version 9.1 (SAS Institute Inc., Cary, NC,
USA). The associations of sleep-related variables with cogni-
tive functioning were analysed by general linear models or
generalized logistic regression models (depending on the
character of the dependent variable continuous categorical).
First, the best model (in terms of r
2
) with sleep-related factors
as explanatory variables and indicator of cognitive functioning
as the dependent variable was found (type I models). Then, the
Table 1 Sleep-related factors as explanatory variables (in general linear models) of objective cognitive tests in the adult general population
Sleep factor
Models explaining performance in word fluency test
Model I Model II Model III
n=5171; df = 7;
r
2
=0.0292
n=5171; df = 11;
r
2
=0.1736
n=5171; df = 24;
r
2
=0.1813
FPFPFP
Fatigue and tiredness 26.0 <0.0001 8.2 0.0003 6.4 0.002
Exceptional tiredness 22.0 <0.0001 3.6 0.026 3.5 0.029
Sleep duration 19.7 <0.0001 7.3 <0.0001 5.5 0.001
Models explaining learning effect
Model I Model II Model III
n=5164; df = 7;
r
2
=0.0378
n=5164; dff = 11;
r
2
=0.3386
n=5164; df = 24;
r
2
=0.3427
FPFPFP
Use of hypnotics 29.5 <0.0001 2.4 0.121 1.0 0.330
Fatigue and tiredness 27.9 <0.0001 9.7 <0.0001 6.8 0.001
Sleep duration 16.1 <0.0001 12.0 <0.0001 9.4 <0.0001
Probable sleep apnoea 11.8 0.0006 0.9 0.336 1.4 0.231
Models explaining recall rate
Model I Model II Model III
n=5149; df = 6;
r
2
=0.0139
n=5149; df = 10;
r
2
=0.1164
n=5149; df = 25;
r
2
=0.1213
FPFPFP
Use of hypnotics 25.1 <0.0001 4.4 0.036 2.6 0.107
Fatigue and tiredness 6.8 0.001 1.1 0.320 0.8 0.469
Sleep duration 5.4 0.001 4.8 0.003 3.7 0.011
Model I is the best (in terms of r
2
) model including only sleep factors as explanatory variables. Model II is adjusted for the sociodemographic
factors (gender, age and education). Model III is adjusted for the sociodemographic factors + health factors (depression, alcohol dependency,
use of neuroleptics, use of antidepressants and 11 diseases).
Sleep duration and cognitive functioning 439
2009 European Sleep Research Society, J. Sleep Res.,18, 436–446
model was adjusted for sociodemographic variables (type II
models) and finally, the model was adjusted for sociodemo-
graphic and health indicators (type III models). In order to
interpret the statistical results yielded by the multivariable
models, post hoc tests between different contrasts within
statistical effects were performed and the multicollinearity
between independent variables (explanatory variables and
covariates) was analysed by calculating SpearmanÕs correlation
coefficients between them.
RESULTS
Sleep-related variables as predictors of cognitive functions
Analyses of the type I models (Table 1) revealed that sleep-
related variables alone accounted for 2.9, 3.8 and 1.4% of the
variance in objective cognitive tests (verbal fluency, learning
effect and recall rate, respectively). However, for subjective
memory function they accounted for 10.2% of variance
(Table 2). Within sleep-related variables, Ôfatigue and tired-
nessÕand sleep duration were independent predictors of
performance in all objective cognitive tests. In addition, verbal
fluency was also predicted independently by Ôexceptional
tirednessÕ, learning effect was predicted by use of hypnotics
and Ôprobable sleep apnoeaÕand recall rate by use of hypnotics.
Subjective memory function was predicted to be statistically
independent by all sleep-related variables.
The analyses of types II and III models (Tables 1 and 2)
revealed that controlling the models for the sociodemographic
factors (type II models) attenuated associations between sleep
and cognitive functioning but did not totally abolish all of
them. Sociodemographic factors (mainly age and education)
also added remarkably (10.2–30.1%) to the variance ac-
counted for objective cognitive tests. In subjective memory
function, sociodemographic factors added 18.8% to the
variance accounted for. Controlling also for health indicators
(type III models) further attenuated the associations of sleep-
related variables with indicators of cognitive functioning, but
only relatively slightly. Health indicators added relatively little
(0.4–0.7%) to the variance of objectively assessed cognitive
functioning and only 1.1% to that of subjectively assessed
memory functioning. Consequently, after all adjustments in
full models (type III models), sleep duration remained asso-
ciated statistically and independently with performance in all
objective cognitive tests, Ôfatigue and tirednessÕremained an
independent statistical predictor of word fluency and learning
effect and exceptional tiredness remained an independent
statistical predictor of word fluency. Statistical and indepen-
dent associations of hypnotic use and probable sleep apnoea
were abolished in type III models. In the full model of
subjective memory function, Ôfatigue and tirednessÕ,Ôexcep-
tional tirednessÕand Ôinsomnia or sleep disorderÕeach
remained associated statistically and independently with
memory complaints. The effect of sleep duration did not quite
reach statistical significance (P=0.054).
Post hoc tests (Table 3) showed that the association of sleep
duration with cognitive functioning was, as expected, U-
shaped. Seven- and 8-hour sleepers outperformed both short
and long sleepers in all three cognitive tests. Short and long
sleepers did not differ statistically in their test performance
when compared with each other. However, when the sleep
duration was considered as a continuous variable and the
correlation coefficients between sleep duration and cognitive
performance (within short and long sleepers separately) were
calculated, there was a stronger Ôdose–responseÕ-like relation-
ship in long sleepers than in short sleepers between sleep
duration and cognitive performance. Specifically, in long
sleepers sleep duration correlated with a verbal fluency of
)0.19, learning effect of )0.21 and recall rate of )0.21. In short
sleepers the corresponding correlations were 0.12, 0.16 and
0.10, respectively. Analogously to objective cognitive tests, but
much more pronounced, the odds for reporting Ôvery good or
goodÕmemory were three- to fourfold lower in short and long
sleepers when compared with 7- and 8-h sleepers. Feelings of
Ôfatigue and tirednessÕwere associated consistently and linearly
with low performance in cognitive tests and a decreased rate of
reporting Ôvery good or goodÕsubjective memory function.
Table 2 Sleep factors as explanatory variables (in generalized logistic regression models) of subjective memory function in the adult general
population (type 3 analysis of effects are shown)
Sleep factor df
Model I Model II Model III
n=5171; r
2
=0.1019 n=5171; r
2
=0.2900 n=5171; r
2
=0.3008
Wald v
2
PWald v
2
PWald v
2
P
Fatigue and tiredness 4 107.1 <0.0001 66.8 <0.0001 46.0 <0.0001
Exceptional tiredness 4 49.1 <0.0001 47.5 <0.0001 42.0 <0.0001
Sleep duration 6 42.6 <0.0001 18.5 0.005 12.4 0.054
Insomnia or sleep disorder 4 28.2 <0.0001 14.7 0.005 10.9 0.028
Use of hypnotics 2 16.3 0.0003 0.6 0.723 0.5 0.768
Probable sleep apnoea 2 12.1 0.002 1.5 0.474 0.9 0.629
Model I is the best (in terms of r
2
) model including only sleep factors as explanatory variables. Model II is adjusted for the sociodemographic
factors (gender, age and education). Model III is adjusted for the sociodemographic factors + health factors (depression, alcohol dependency,
use of neuroleptics, use of antidepressants and 11 diseases).
440 E. Kronholm et al.
2009 European Sleep Research Society, J. Sleep Res.,18, 436–446
Complaints of exceptional tiredness were associated with lower
verbal fluency and lower rate of reporting Ôvery good or goodÕ
memory function. Complaints of Ôinsomnia or sleep disorderÕ
were associated independently only with a decreased rate of
reporting Ôvery good or goodÕsubjective memory function; this
insomnia complaint was not associated with changes in
objective cognitive tests.
SpearmanÕs rank order correlation coefficients were calcu-
lated between all independent variables used in our models
(Table 4). However, in order to simplify the correlation
matrix, different reported illnesses were not included as
separate variables. In the correlation matrix they were substi-
tuted by a single variable indicating the presence or absence of
any illness. (Sleep duration was considered in Table 4 as a
continuous variable; because a U-shaped association was
expected between sleep duration and other independent
variables, the correlation coefficients were calculated sepa-
rately for both ends of the sleep duration distribution.) Table 4
shows that, as expected, there was multicollinearity between
independent variables. For instance, short sleep was associated
with insomnia or sleep disorder which, in turn, was associated
with feelings of tiredness, use of hypnotics, depression, use of
antidepressants and age. Long sleep was associated with
feelings of tiredness and reported illnesses.
In addition, we performed the above-mentioned multivar-
iable models among those participants who did not report any
illness and who also reported good or relatively good
subjective health (n=2201) (detailed results are not shown).
Of these, 11.0% were short sleepers and 8.8% long sleepers.
Thus, only about 30% of short and long sleepers belonged to
this healthy subgroup. Results of these analyses revealed that
in type I models Ôexceptional tirednessÕ(for word fluency),
Ôprobable sleep apnoeaÕ(for word fluency, learning effect and
subjective memory function), sleep duration (for learning
effect) and insomnia or sleep disorders (for subjective memory
function) were associated statistically independently with
cognitive functioning. However, after adjustments for socio-
economic factors (type II models) only Ôexceptional tirednessÕ
(for word fluency), insomnia and sleep disorders and probable
sleep apnoea (for subjective memory function) reached statis-
tical significance.
We also analysed the associations between objective cogni-
tive tests and subjective assessment of memory function. The
subjective assessment of the memory function that accounted
for the variance of objective testing are as follows: 8.6% of
word fluency, 14.2% of learning effect and 7.4% of recall rate.
DISCUSSION
Our main finding was that, in a general adult population,
sleep-related factors (short and long sleep duration, fatigue
and tiredness and exceptional tiredness) were independent
statistical predictors of low objectively measured cognitive
functioning, even after control for pertinent health and
socioeconomic factors. In addition, insomnia-related symp-
toms predicted decreased subjective memory function inde-
Table 3 Post hoc tests between the different contrasts within statistical effects yielded by the multivariable model type I
Sleep-related predictor variable n
Mean test score (±SD)
Subjective memory function
Ôgood or very goodÕ(%)
Verbal fluency Learning effect Recall rate
Sleep duration
Short sleepers (1) 759 23.3 ± 6.9
(2,3)
20.2 ± 4.4
(2,3)
84.3 ± 15.4
(2,3)
7.0
(2,3)
7-h sleepers (2) 1862 24.8 ± 6.9 21.3 ± 3.9 86.4 ± 14.8 22.4
8-h sleepers (3) 1940 24.6 ± 7.2 21.2 ± 4.3 85.7 ± 15.2 23.5
Long sleepers (4) 599 22.6 ± 7.2
(2,3)
20.0 ± 5.3
(2,3)
83.1 ± 19.0
(2,3)
5.8
(2,3)
Fatigue and tiredness
No or quite little (1) 3520 24.8 ± 7.0
(2,3)
21.3 ± 4.1
(2,3)
86.1 ± 14.9
(2,3)
45.3
(2,3)
To some extent (2) 1174 23.7 ± 7.1
(3)
20.5 ± 4.4
(3)
84.8 ± 15.7
(3)
10.0
(3)
Much or very much (3) 477 21.6 ± 7.0 19.3 ± 5.0 82.0 ± 19.4 3.4
Exceptional tiredness
No (1) 3042 24.8 ± 7.1
(2,3)
38.9
(2,3)
Cannot say (2) 1315 23.4 ± 6.9 12.3
Yes, often or nearly always (3) 814 23.4 ± 7.1 7.3
Probable sleep apnoea
No (1) 4748 21.0 ± 4.3
(2)
54.7
(2)
Yes (2) 412 20.1 ± 4.1 3.8
Use of hypnotics
No (1) 4829 21.1 ± 4.3
(2)
85.8 ± 15.3
(2)
56.3
(2)
Yes (2) 331 19.2 ± 4.7 80.3 ± 18.3 2.2
Insomnia or sleep disorder
No or quite little (1) 3398 42.9
(2,3)
To some extent (2) 1143 10.8
(3)
Much or very much (3) 622 4.8
Different classes (answering modes) of each predictor variable are numbered in the first column. These numbers are then used in other columns
to indicate the significant (P< 0.05) contrasts when the mean or proportion for a given class is compared with other classes of its variable.
Sleep duration and cognitive functioning 441
2009 European Sleep Research Society, J. Sleep Res.,18, 436–446
pendently. However, sleep-related factors alone accounted for
only a small part of the variation in objective cognitive tests
(1.4–3.8%), but accounted for 10.2% of the variation in
subjective memory function. Accordingly, objective cognitive
tests and subjective memory function shared relatively little
common variance (7.4–14.2%). Consequently, although both
objective and subjective cognitive functioning were associated
with sleep factors, they can be interpreted as relatively different
dimensions of functional ability of an individual, with self-
reported sleep-related factors being related more to subjective
than objective cognitive functioning.
Our main interest in this study was evaluation of self-
reported sleep duration. We focused upon this parameter
because of the increasing evidence of the morbidity and
mortality risks associated with short and long self-reported
sleep duration [for reviews on this topic, see Grandner and
Drummond (2007) and Youngstedt and Kripke (2004)]. Short
and long sleep duration may thus be either detrimental for an
individualÕs functional state or a non-causal indicator of
worsened functional state. Consequently, we assumed that
short and long sleep duration should be associated with
cognitive functioning in the general population. To our
knowledge, this is the first study to show this correlation in a
large sample representing the general adult population.
The association of short sleep with decreased cognitive
performance can be interpreted as supporting the existence of
partial sleep deprivation in short sleepers. However, this does
not explain the association of long sleep duration with decreased
cognitive function. In a recent review (Grandner and Drum-
mond, 2007), seven possible mechanisms underlying the rela-
tionship between excessive sleep length and elevated mortality
risk were discussed. Of these mechanisms, sleep fragmentation,
fatigue and underlying disease are relevant to our study.
Obstructive sleep apnoea syndrome (OSAS), which is charac-
terized by frequently interrupted sleep, is one of the most
obvious potential mechanisms underlying sleep fragmentation.
OSAS has been shown to contribute to deterioration in various
cognitive functions such as verbal fluency (Bedard et al., 1991).
We found that Ôprobable sleep apnoeaÕwas not associated
independently with cognitive functioning in our fully adjusted
models. It was an independent predictor of the learning effect
when only sleep-related factors were included in the model.
However, the control of socioeconomic factors (gender, age and
education) removed its effect from the model. Notably, feeling
non-energetic or tired Ôquite or very muchÕincreased the odds of
probable sleep apnoea 2.5-fold when compared with feeling non-
energetic or tired Ônot at all or quite littleÕ. Therefore, we feel that
although we had no information on polysomnographically
determined OSAS in our models, the linear combination of the
variables Ôpossible sleep apnoeaÕand feeling Ônon-energetic or
tiredÕprovided information reflecting the effect of possible
OSAS in our statistical models. The higher educational level
decreased the odds of probable sleep apnoea 1.4-fold when
compared with basic educational level. Compared with female
gender, male gender increased the odds of probable sleep apnoea
4.8-fold. Thus, our results do not suggest that there is no
association between probable sleep apnoea and cognitive
functioning, but that its statistical influence (if present) was
directed via tiredness and socioeconomic factors in our fully
adjusted models.
Further, OSAS has been suggested to be more prevalent in
long sleepers compared with other sleep duration groups
(Bliwise et al., 1994). However, in our study sample, Ôprobable
sleep apnoeaÕwas distributed evenly across all sleep duration
groups: the overall prevalence rate was approximately 8%.
Thus, the statistical influence of long sleep duration on
cognitive functioning in our models cannot be explained by
OSAS.
Table 4 SpearmanÕs correlation coefficients among independent variables in models I, II and III
1234567891011121314
Sleep duration (1)
Short and 7-h sleepers 1.00 )0.18 )0.17 )0.01 )0.26 )0.14 )0.06 )0.05 )0.05 )0.04 0.01 0.15 )0.13 0.14
Mid-range and long sleepers 1.00 0.14 0.16 0.02 0.02 0.05 0.08 0.13 0.01 0.13 0.06 )0.09 0.07 )0.16
Fatigue and tiredness (2) 1.00 0.45 0.06 0.51 0.18 0.23 0.18 0.06 0.09 0.13 )0.12 0.13 )0.25
Exceptional tiredness (3) 1.00 0.12 0.34 0.16 0.17 0.16 0.05 0.09 0.00 )0.11 0.07 0.03
Probable sleep apnoea (4) 1.00 0.05 0.03 0.01 0.03 0.03 0.02 )0.19 )0.06 0.06 )0.07
Insomnia or sleep disorder (5) 1.00 0.30 0.21 0.16 0.08 0.08 0.09 )0.11 0.20 )0.22
Hypnotics (6) 1.00 0.12 0.21 0.03 0.16 0.05 )0.06 0.18 )0.16
Depression (7) 1.00 0.26 0.06 0.14 0.08 0.03 )0.06 )0.05
Antidepressants (8) 1.00 0.03 0.18 0.07 )0.02 0.05 )0.13
Alcohol Dependency (9) 1.00 0.06 )0.14 0.03 )0.07 0.04
Neuroleptics (10) 1.00 0.04 )0.04 0.04 )0.11
Gender (11) 1.00 0.05 0.04 )0.04
Education (12) 1.00 )0.42 0.24
Age (13) 1.00 )0.38
Any reported diagnosis (14) 1.00
Because of the large number of observations all coefficients 0.03 are statistically significant (P< 0.05). Therefore, Pvalues have no practical
meaning and they are not shown. Sleep duration is considered as a continuous variable: short and 7-h sleepers = participants reporting sleep
duration £7 h; mid-range and long sleepers = participants reporting sleep duration 8h.
442 E. Kronholm et al.
2009 European Sleep Research Society, J. Sleep Res.,18, 436–446
Tiredness or fatigue is another potential mechanism explain-
ing the relationship between long sleep duration and impaired
cognitive functioning. In our earlier study we reported that
Ôexceptional tirednessÕas well as being Ônon-energetic or tiredÕ
were, to an equal extent, more prevalent among both short and
long sleepers than among mid-range sleepers (Kronholm et al.,
2006). Thus, it seems that long sleepers do not benefit from
their long sleep duration when compared with mid-range
sleepers or even with short sleepers. This may indicate that self-
reported long sleep time is associated with failure of the
restorative function(s) of sleep that subsequently affects
cognitive functioning. Increased tiredness can be due to a
variety of psychological and somatic conditions (e.g. periodic
leg movements during sleep) that may also make oneÕs sleep
fragmented, even without the presence of OSAS. Previous
laboratory studies have shown that even minor arousals in
sleep that do not change the sleep architecture to any great
extent lead to an increase in sleepiness the following day [for a
review, see Bonnet and Arand (2003). However, it should be
mentioned that the two indicators of tiredness we used in our
models should be interpreted as more reflective of feelings of
fatigue and tiredness than sleepiness. It has been suggested that
fatigue and sleepiness may be relatively independent conse-
quences of sleep disorders (Hossain et al., 2005) and organic
diseases (Merkelbach et al., 2006). In this study exceptional
tiredness and feeling non-energetic or tired were, as expected,
related strongly to one another. Despite this, they were both
associated statistically independent with low performance in
word fluency testing. In learning effect, only fatigue and
tiredness remained an independent statistical predictor of test
performance, suggesting that the statistical effect of excep-
tional tiredness was directed via fatigue and tiredness in this
model. However, control for these factors did not remove the
statistical effect of sleep duration on cognitive performance in
any model. An important conclusion is that, although feelings
of tiredness are associated with decreased cognitive perfor-
mance in the general population, they do not explain the
association of sleep duration with cognitive functioning. Thus,
it is likely that the decreased performance of long sleepers
cannot be explained entirely as a result of their sleep
disruption. An interesting and somewhat unexpected finding
was that there was a stronger dose–response-like association
between sleep duration and objective cognitive performance in
long sleepers than in short sleepers. This was most evident in
the test of delayed recall, where the correlation between sleep
duration (considered here as a continuous variable) and test
performance was 0.10 in short sleepers and )0.21 in long
sleepers. Consequently, the longer the sleep duration in long
sleepers the more detrimental effect it had on test performance.
It has been suggested previously that increased daytime
sleepiness predicts declining cognitive function (Cohen-Zion
et al., 2001). Taking into account that in our earlier report
(Kronholm et al., 2006) we found a stronger dose–response-
like association between sleep duration and feelings of tired-
ness and fatigue among long sleepers than among short
sleepers, it might be possible that predementia syndrome
(Geerlings et al., 1999) may be predicted by self-reported
habitual long sleep. In these cases, impaired sleep function
leading to daytime tiredness and long sleep would be due to an
underlying degenerative neurological disease. In other words,
during ageing, general processes of the brain may be reflected
earlier in sleep factors and only later in cognitive declining.
This is, at present, a purely speculative hypothesis requiring
elucidation in future studies.
Important modulating factors of cognitive functioning are
way of life and living conditions of an individual. As reported
earlier (Kronholm et al., 2006) in the Health 2000 sample (of
which the current study sample is a part), in long sleepers the
unemployment and being at home is more prevalent than in
short- and mid-range sleepers; consequently, long sleepers take
part in working life less frequently than short- and mid-range
sleepers. However, this difference is not explained by rate of
retirement, which does not differ significantly between short
and long sleepers. In addition, living alone is more prevalent in
short and long sleepers than mid-range sleepers. Thus, self-
reported long sleep in particular may be associated with a
passive way of life, which may in turn influence cognitive
ageing. It is also interesting to note that differences between
habitual sleep duration in the general population may partly
reflect the variability in an individual circadian pacemakerÕs
programme (Aeschbach et al., 2003), causing longer intervals
with high plasma melatonin levels in long sleepers than in
other individuals. This, in turn, may have an inhibitory effect
on memory formation (Rawashdeh et al., 2007) in long
sleepers.
This finding is in line with the results of Schmutte et al.
(2007) concerning elderly people, and also supports the
hypothesis that the sleep of long sleepers is not equally
restorative to that of mid-range sleepers. An alternative or
complementary explanation is that short sleepers may tolerate
a high degree of sleep pressure better than other individuals
(Aeschbach et al., 2001), which makes differences in cognitive
performance more robust between long and mid-range sleepers
than between short- and mid-range sleepers.
Although we found an independent association between self-
reported sleep duration with cognitive functioning in the
general adult population, it should be emphasized that sleep-
related factors accounted for only a small part of the variation
in cognitive functioning. There are probably several reasons
for this finding. As expected, the main explanatory variables
were socioeconomic factors, particularly education and age.
The interesting finding was that health-related factors added
very little to the explanatory power of the models when they
were added after sleep-related factors. It is evident that some
part of the cognitive effects of health-related factors was
expressed via sleep-related variables. For example, short sleep
was associated with insomnia, which was associated in turn
with depression. In addition, short sleepers reported arthrosis,
cerebrovascular diseases, coronary artery disease and hyper-
tension more often than did mid-range sleepers. Long sleep
was associated with use of neuroleptics. In addition, long
sleepers reported cerebrovascular and other diseases of the
Sleep duration and cognitive functioning 443
2009 European Sleep Research Society, J. Sleep Res.,18, 436–446
circulatory system and diabetes more often than did mid-range
sleepers. However, this shared effect between sleep- and health-
related factors did not abolish the statistically independent
(although relatively small) association of sleep-related factors
with cognitive performance. It is highly probable that among
both short and long sleepers there are individuals who are so-
called ÔnaturalÕshort and long sleepers without any functional
defects. The presence of these individuals within the study
population will diminish the association of sleep duration with
cognitive functioning in the remainder of the population. This
suggestion was supported by separate analyses in a subgroup
of participants with good subjective health without any known
diseases. In this subgroup, after adjusting for the sociodemo-
graphic variables the statistically independent association of
sleep factors with cognitive functioning in objective tests was
abolished (in case of probable sleep apnoea and sleep
duration) but preserved in case of exceptional tiredness.
However, for subjective cognitive functioning, independent
statistical effects of probable sleep apnoea and insomnia or
sleep disorder were preserved even after adjustments.
It is noteworthy that some, although relatively small,
independent associations of sleep factors with cognitive
functioning were found even in the healthy proportion of the
population. However, the independent effect of sleep duration
was not found in this proportion of the population. This result
may come partially from a relatively small number of short
and long sleepers among healthy participants. Another reason
for the relatively small association between sleep duration and
objective cognitive performance is probably the relative
simplicity of our performance tests. The easiness of a perfor-
mance test may mask minor or moderate differences in
cognitive functions between various sleep duration groups
(Blatter et al., 2005).
In contrast to the objective cognitive tests, sleep-related
factors accounted for a greater part of the variance in self-
assessment of memory function (1.4–3.8% versus 10.2%,
respectively). In addition, self-assessed memory function was
the only dependent variable where insomnia-related symptoms
were associated independently with memory function, even
after control for other variables. Again, adding the health
indicators after the sleep factors did not increase the explan-
atory power of the model. The control of socioeconomic
factors abolished the independent statistical effects of hypnot-
ics and probable sleep apnoea. When taking into account that
subjective memory function and objective cognitive tests
shared very limited common variance (7.4–14.2%), it is evident
that objective cognitive performance and subjective cognitive
functional ability are relatively different dimensions. It seems
logical to suggest that subjective sleep complaints are inter-
linked introspectively with the individualÕs general health
condition and his her subjective functional ability. However,
awareness of their objective consequences may be incomplete.
Consequently, self-reported sleep duration can be interpreted
partially as reflecting more strongly subjective symptom
formation rather than physiological sleep amount per se
(Jean-Louis et al., 2000; Kripke, 2004).
Study limitations
There are some limitations concerning our study which need
further consideration. First, it is clear that the cross-sectional
design cannot confirm causal relationships. A second limita-
tion is that our study evaluated self-reported sleep duration,
and thus our results may not be generalized to reflect the
physiological sleep duration, as measured by polysomnogra-
phy. Self-reported sleep duration may be more of a measure of
habitual bed-rest duration (Jean-Louis et al., 2000; Kripke,
2004) and may not be associated with slow-wave sleep
(Klerman and Dijk, 2005). Another limitation in the measure
of self-reported sleep duration in our study is a lack of
information on its subjective sufficiency and failure to distin-
guish night sleep amount from daytime sleep amount.
Although we feel that including feelings of tiredness and
fatigue as well as exceptional tiredness in our models may have
partly accounted for these limitations, in future studies these
dimensions in sleep experience and behaviour should be taken
into account more thoroughly. Using self-reported estimates of
sleep duration may have influenced our results in another way:
a certain cognitive capacity is required for the completion of
different questionnaires. Consequently, more participants with
intact cognitive capacity than participants with impaired
cognitive capacity have been probably selected for the final
analysis sample. This implies that the association with sleep
duration and cognitive ability may be somewhat underesti-
mated in this study. Furthermore, our method of operation-
alizing major depressive episodes can be criticized. It has been
suggested that depressive and bipolar disorders have different
effects on cognitive deficits (Paradiso et al., 1997). Thus,
combining these patients into a single group may have affected
the independence of sleep-related factors in our models.
However, the prevalence and incidence rates of bipolar
disorders are clearly lower in Finland than, for example, in
western-type societies, on average (Kieseppa
¨et al., 2004;
Pera
¨la
¨et al., 2007); thus, it is likely that in the present study
a majority, if not all, of the said individuals with a history of
major depressive episodes actually had major depressive
disorder. It is also clear that the statistical independence of a
given risk factor always depends upon the variables included in
the model and the very term Ôindependent risk factorÕhas a
meaning in the context of a particular statistical model only
(Brotman et al., 2005).
CONCLUSIONS
Our study shows that the self-reported sleep-related factors
(short and long habitual sleep duration and their daytime
consequences) are associated with objectively assessed and self-
reported decreased cognitive functioning. The association is
stronger between sleep factors and subjective cognitive func-
tion than objective cognitive tests. This finding can be
interpreted to mean that self-reported sleep duration and its
daytime consequences may reflect both actual realization of
the restorative function of sleep and symptom formation in the
444 E. Kronholm et al.
2009 European Sleep Research Society, J. Sleep Res.,18, 436–446
context of an individualÕs health status. In terms of public
health, different measures are required to amend the situation.
Short sleepers should probably be provided with the means to
increase their sleep time, while long sleepers would probably
benefit from the means to improve their sleep quality.
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... In the past years, most studies focused on memory complaints while ignoring other areas of cognition and demonstrated that there was a non-linear correlation between sleep duration and objective cognitive decline [25,26]. It was found that individuals with short sleep duration or long sleep duration tended to report worse memory complaints [25,27]. ...
... In the past years, most studies focused on memory complaints while ignoring other areas of cognition and demonstrated that there was a non-linear correlation between sleep duration and objective cognitive decline [25,26]. It was found that individuals with short sleep duration or long sleep duration tended to report worse memory complaints [25,27]. Apart from memory, few studies have focused on other cognitive domains such as executive function. ...
... Earlier study found a non-linear association between cognitive impairment and sleep duration [25,37], which was similar to our findings. A longitudinal analysis based on women showed a V-shaped association between higher MCI/dementia risk and sleep duration, indicating both shorter (< 6 h) and longer (> 8 h) sleep duration associated with higher risk of cognitive decline [26]. ...
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Background Subjective cognitive decline (SCD) may be the early screening signal to distinguish susceptible population with Alzheimer’s disease (AD) and mild cognitive impairment (MCI). Subjective cognitive complaints (SCCs) have been proved strongly associated with SCD. This study aimed to explore the association between sleep duration and SCCs in the Chinese elderly. Methods We conducted a cross-sectional study involving 688 participants aged 60 years and older in Guangdong Province, China. SCCs were assessed by the Subjective Cognitive Decline questionnaire 9 (SCD-Q9), which contained 9 items with two dimensions, including the overall memory function and time comparison (OMTC) and daily activity ability (DAA). Restricted cubic splines and generalized additive model (GAM) were used to fit the association between sleep duration and SCD-Q9 score. Results There were significant U-shaped associations between sleep duration and overall score of SCD-Q9 ( EDF = 3.842, P < 0.001), as well as the OMTC dimension ( EDF = 4.471, P < 0.001) in the age- and gender-adjusted GAM. The lowest points on the overall score of SCD-Q9 and OMTC score were observed in those sleeping 8 h per night. After further adjusting for other demographic characteristics, lifestyle behaviors, hypertension and diabetes, the U-shaped associations between sleep duration and the overall score of SCD-Q9 ( EDF = 3.575, P = 0.004), sleep duration and the OMTC score ( EDF = 4.478, P = 0.010) were still found. The daily activity ability (DAA) score was also non-linear associated with sleep duration both in the age- and gender-adjusted GAM ( EDF = 2.314, P < 0.001) and further adjusted GAM ( EDF = 2.080, P = 0.010). Conclusions Both longer sleep duration (> 8 h) and shorter duration (< 8 h) were linked to worse SCCs. Future studies should explore the protective effect of managing sleep duration on SCD and its progression to dementia.
... Sleep restriction is a facet of modern life that jeopardizes the cognitive performance including lapses of attention, slowed working memory, reduced cognitive throughput, and perseveration of thought 2 . An epidemiological study demonstrated that short and long sleep duration were associated with both objectively assessed and self-reported decreases in cognitive function in the general population 3 . In particular, the adverse effects of a short sleep duration on cognitive function have been well studied [2][3][4][5] . ...
... An epidemiological study demonstrated that short and long sleep duration were associated with both objectively assessed and self-reported decreases in cognitive function in the general population 3 . In particular, the adverse effects of a short sleep duration on cognitive function have been well studied [2][3][4][5] . However, there has been no consensus regarding the impacts of sleep structure and sleep fragmentation on working memory. ...
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Introduction: Sleep is essential for performing cognitive function in humans. We have hypothesized that sleep fragmentation compared to sleep efficiency may have a negative impact on the working memory. Material and Methods: Twenty-eight healthy adults (18 males and 10 females; mean age 27.8±15.5 years) were enrolled in this study. We measured the total sleep time (TST), sleep efficiency, %stage wakefulness (W), %stage rapid eye movement (REM), %stage N1, %stage N2, %stage N3, wake after sleep onset (WASO), and arousal index using polysomnography. Working memory, executive function, and sustained attention of three domains of cognitive function were evaluated with the number of back task (N-back task), Wisconsin card sorting test (WCST), and continuous performance test-identical pairs (CPT-IP), respectively. Results: The percentage of correct answers on the 2-back task was significantly correlated with %stage REM, %stage N1, and %stage N2 (%stage REM: r=0.505, p=0.006; %stage N1: r=-0.637, p
... Sleep duration, although mostly assessed by self-reports, may be seen as a more objective measure than sleep quality ; thus, they might measure different aspects of the sleep experience. Moreover, previous work have suggested a u-shaped relationship where too short and too long sleep duration (that is less, or more, than 7-8 h per night) are associated with impaired executive functioning (Kronholm et al., 2009;Wild et al., 2018) and negative mood (Hyakutake et al., 2016;Ohayon et al., 2013). However, non-linear models that would have captured u-shaped associations were not examined in the included studies. ...
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Despite an upsurge of research on spontaneous cognition, little is known about its associations with sleep-related outcomes. This systematic review, following PRISMA guidelines, examined the relationship between sleep and spontaneous thoughts, across different definitions and measurements of sleep outcomes and spontaneous cognition, and a diversity of methodologies. Twenty-one articles with survey and/or experimental designs were identified. Self-reported disturbed sleep-comprising poor sleep quality, more insomnia symptoms, more daytime sleepiness and a tendency towards eveningness-and experimentally induced sleep deprivation were associated with a tendency to engage in disruptive mind wandering and daydreaming, but not positive-constructive daydreaming. Findings regarding circadian fluctuation in spontaneous thoughts were mixed and inconclusive. This systematic review bridges the gap between the sleep and spontaneous cognition research by contributing to the understanding of potential psychological and cognitive mechanisms of spontaneous cognition, as well as by elucidating the emotional and cognitive consequences of disturbed sleep.
... 35 Firstly, a large number of investigations have shown that poor sleep quality is related to poor cognitive performance, such as processing speed, episodic memory recall, and executive function in the elderly. [36][37][38][39] The link between sleep and neurodegenerative disease might be bi-directional; sleep disturbance serves not only as a marker but a promoter of cognitive impairment. Their mutual influence in many aspects is of great significance to the diagnosis and treatment of cognitive deterioration. ...
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Objective: This study aimed to examine the relationship between cognitive function and depressive symptoms and to explore the mediating role of sleep quality in the cognition-depression relationship in Chinese older adults (OAs). Methods: Data came from a nationally representative sample of 16,209 Chinese OAs (aged 65+) from 2008, 2011, 2014, and 2018 waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). A random intercept cross-lagged panel model (RI-CLPM) combined with mediation analysis was adopted to determine the relationship between cognitive function and depressive symptoms and the mediating effect of sleep quality on the ascertained cognition-depression relationship. Results: Poorer cognitive function at prior assessment points were significantly associated with severe depressive symptoms at subsequent assessments, and vice versa. Sleep quality partially mediated the prospective relationship of cognition on depressive symptoms, which accounted for 3.92% of the total effect of cognition on depression. Discussion: Cognitive decline may predict subsequent depressive symptoms, and vice versa. The impact of cognition on depression is partially explained by its influence on sleep quality. Multidisciplinary interventions aimed at reducing depression and cognitive decline per se as well as improving sleep quality would be beneficial for emotional well-being and cognitive health in OAs.
... For example, extremes of overnight sleep duration are related to worse cognition in middle-to-late life individuals. Findings have associated sleeping too short [5][6][7] , too long [8][9][10] or both as being detrimental [11][12][13] while some studies did not show a significant relationship with sleep duration and cognition 14,15 . The strength of the inferences from these studies have been limited, however, due to small sample size or relatively insensitive cognitive measures. ...
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Sleep is essential for life, including daily cognitive processes, yet the amount of sleep required for optimal brain health as we grow older is unclear. Poor memory and increased risk of dementia is associated with the extremes of sleep quantity and disruption of other sleep characteristics. We examined sleep and cognitive data from the UK Biobank (N = 479,420) in middle-to-late life healthy individuals (age 38–73 years) and the relationship with brain structure in a sub-group (N = 37,553). Seven hours of sleep per day was associated with the highest cognitive performance which decreased for every hour below and above this sleep duration. This quadratic relationship remained present in older individuals (>60 years, N = 212,006). Individuals who sleep between six-to-eight hours had significantly greater grey matter volume in 46 of 139 different brain regions including the orbitofrontal cortex, hippocampi, precentral gyrus, right frontal pole and cerebellar subfields. Several brain regions showed a quadratic relationship between sleep duration and volume while other regions were smaller only in individuals who slept longer. These findings highlight the important relationship between the modifiable lifestyle factor of sleep duration and cognition as well as a widespread association between sleep and structural brain health. Tai et al. examine sleep, cognitive and brain imaging data from middle-to-late life healthy individuals from the UK Biobank. They show that between six and eight hours of sleep duration is associated with the highest cognitive performance and larger grey matter volume in several areas of the brain.
... Large epidemiologic studies have shown that short and long sleep duration, [4][5][6][7][8] sleep disturbances, 9 and late sleep timing 10 contribute to adverse health outcomes, including those that are cardiovascular, metabolic, immunological, and psychiatric in nature. [4][5][6][7][11][12][13][14] Current sleep duration recommendations for adults from the National Sleep Foundation include 7-9 h of undisrupted sleep at night. 15 Indicators of good sleep quality include 85% sleep efficiency, a sleep onset latency duration of ≤15 min, and a wake after sleep onset duration of ≤20 min. ...
Article
Background: Patients supported with home parenteral nutrition (HPN) often report poor sleep, however, limited research has been conducted to objectively measure sleep patterns of HPN-dependent patients. Methods: We aimed to characterize the sleep patterns of patients on HPN through 7-day actigraphy in a home-based observational study. Sleep measures of clinical importance were derived from actigraphy including sleep duration, sleep efficiency, sleep onset latency, and wake after sleep onset. Participants also completed validated sleep surveys. Results: 20 participants completed all study procedures [mean (standard deviation): age =51.6 (13.9), BMI =21.4 kg/m2 (4.6), 80% female]. The population median (interquartile range) for sleep duration, sleep efficiency, sleep onset latency, and wake after sleep onset was 6.9 (1.1) hours, 83.3 (7.8) %, 11.8 (7.1) minutes and 57.2 (39.9) minutes, respectively, and 55%, 60%, 35%, and 100% of participants did not meet the recommendations for these measures from the National Sleep Foundation. 65% of participants reported napping at least once during the 7-day period. Based on the Insomnia Severity Index, 70% of participants were classified as having sub-threshold or more severe insomnia. Based on the Pittsburgh Sleep Quality Index, 85% were classified as having significant sleep disturbance. Conclusions: Most HPN-dependent patients likely have disrupted sleep largely driven by difficulty maintaining sleep. The extent to which HPN contributed to poor sleep cannot be elucidated from this observational study. Addressing known factors that contribute to poor sleep and encouraging sleep hygiene and sleep interventions are imperative to improve the overall quality of life of patients requiring HPN. This article is protected by copyright. All rights reserved.
... Insufficient and poor-quality sleep are associated with negative health outcomes, such as overweight and obesity (Vargas, Flores, & Robles, 2014), worsening cognitive function (Beebe, Field, Milller, Miller, & Leblond, 2017;Kronholm et al., 2009), higher mortality rates (Gallicchio & Kalesan, 2009), and cardiovascular diseases (Clark et al., 2016). Poorer sleep quality is also associated bidirectionally with mental health outcomes such as depression and anxiety (Fang, Tu, Sheng, & Shao, 2019;Tavernier & Willoughby, 2014), as well as reduced life satisfaction (Lemola, Ledermann, & Friedman, 2013). ...
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Media use has been linked to sleep disturbance, but the results are inconsistent. This study explores moderating conditions. A media diary study with 58 free‐living adults measured the time spent with media before bed, the location of use, and multitasking. Electroencephalography (EEG) captured bedtime, total sleep time, and the percent of time spent in deep (Stage N3), and rapid eye movement (REM) sleep. Media use in the hour before sleep onset was associated with an earlier bedtime. If the before bed use did not involve multitasking and was conducted in bed, that use was also associated with more total sleep time. Media use duration was positively associated with (later) bedtime and negatively associated with total sleep time. Sleep quality, operationalised as the percent of total sleep time spent in N3 and REM sleep, was unaffected by media use before bed. Bedtime media use might not be as detrimental for sleep as some previous research has shown. Important contextual variables moderate the relationship, such as location, multitasking, and session length.
... These aspects are crucial for individuals' psychological functioning as sleep supports different cognitive processes involved in daily functioning (Waters and Bucks, 2011). For instance, sleep duration has been linked to verbal fluency and list memory, with both long and short sleepers having poorer performance in such kinds of tasks (Kronholm et al., 2009). Sleeping less than 5 h a night has been correlated with poorer global cognition and poorer performance in verbal memory, verbal fluency, and working memory (Tworoger et al., 2006). ...
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Sleep problems are increasingly present in the general population at any age, and they are frequently concurrent with-or predictive of-memory disturbances, anxiety, and depression. In this exploratory cross-sectional study, 54 healthy participants recruited in Naples (Italy; 23 females; mean age = 37.1 years, range = 20-68) completed the Pittsburgh Sleep Quality Index (PSQI) and a neurocognitive assessment concerning both verbal and visuospatial working memory as well as subjective measures of anxiety and depression. Then, 3T fMRI images with structural and resting-state functional sequences were acquired. A whole-brain seed-to-seed functional connectivity (FC) analysis was conducted by contrasting good (PSQI score <5) vs. bad (PSQI score ≥5) sleepers. Results highlighted FC differences in limbic and fronto-temporo-parietal brain areas. Also, bad sleepers showed an anxious/depressive behavioural phenotype and performed worse than good sleepers at visuospatial working-memory tasks. These findings may help to reveal the effects of sleep quality on daily-life cognitive functioning and further elucidate pathophysiological mechanisms of sleep disorders.
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Little is known regarding sleep's association with the traditional developmental course of late-life cognitive functioning. As the number of older adults increases worldwide, an enhanced understanding of age-related changes in sleep and cognition is necessary to slow decline and promote optimal aging. This review synthesizes the extant literature on sleep and cognitive function in healthy older adults, older adults with insomnia, and older adults with sleep apnea, incorporating information on the potential promising effects of treating poor sleep on cognitive outcomes in older adults. Unifying theories of the sleep-cognition association, possible mechanisms of action, and important unanswered questions are identified.
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Objectives We applied a person-oriented approach and used latent class linear mixed models to identify sleep trajectories that explain memory, concentration, and learning ability problems after retirement. Methods Data consist of prospective surveys from four phases of the Helsinki Health Study between 2000–2017 (n = 3748, aged 55–77 years, 80% women). Multinomial regression was used to examine the associations between sleep trajectories and cognitive function, adjusting for sociodemographic, health-related behavior, and health factor covariates. Results Among statutory retirees, three latent group trajectories of insomnia-related symptoms were identified: stable low, decreasing, and increasing. Among those who had retired for disability reasons, we identified one additional latent group trajectory: stable high. Insomnia symptoms were associated with worse cognitive function. Discussion Early detection of insomnia symptoms would be a potential intervention point to improve both sleep quality and prevent cognitive decline in later life. However, intervention studies are needed.
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Objective: The few studies of bipolar I disorder in twins have consistently emphasized the genetic contribution to disease liability. The authors report what appears to be the first twin study of bipolar I disorder involving a population-based twin sample, in which the diagnoses were made by using structured, personal interviews. Method: All Finnish same-sex twins (N=19,124) born from 1940 to 1957 were screened for a diagnosis of bipolar I disorder as recorded in the National Hospital Discharge Register between 1969 and 1991 or self-reported in surveys of the Finnish Twin Cohort in 1975, 1981, and 1990. Thirty-eight pairs were thereby identified and invited to participate in the study; the participation rate was 68%. Lifetime diagnoses were made by using the Structured Clinical Interview for DSM-IV. The authors calculated probandwise and pairwise concordances and correlations in liability and applied biometrical model fitting. Results: The probandwise concordance rates were 0.43 (95% CI=0.10 to 0.82) for monozygotic twins and 0.06 (95% CI=0.00 to 0.27) for dizygotic twins. The correlations in liability were 0.85 and 0.41, respectively. The model with no familial transmission was rejected. The best-fitting model was the one in which genetic and specific environmental factors explained the variance in liability, with a heritability estimate of 0.93 (95% CI=0.69 to 1.00). Conclusions: The high heritability of bipolar disorder was demonstrated in a nationwide population-based twin sample assessed with structured personal interviews.
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Several studies have suggested that individuals with long or short sleep durations are at greater risk for adverse outcomes relative to individuals sleeping 7–8 hours a night. The mechanisms leading to these results have never been fully explained, but individual differences in how long an individual sleeps are usually considered to reflect lifestyle rather than disease. Alternatively, individuals may sleep a particular amount because of characteristics of their sleep physiology. In this study, we examined population-based data on the associations between sleep duration and several symptoms of sleep-related disease, reported snoring and daytime sleepiness. Results from 1877 independently living individuals between the ages of 50 and 65 years suggested that long, but not short, sleep durations were related to greater reported snoring. Higher levels of reported snoring and daytime sleepiness, but not habitual sleep duration, were related to measures of disease and lower psychosocial function. We suggest that future epidemiologic studies use such additional items as potential indicators of sleep-related disease.
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The Consortium to Establish a Registry for Alzheimer's Disease (CERAD) was funded by the National Institute on Aging in 1986 to develop standardized, validated measures for the assessment of Alzheimer's disease (AD). The present report describes the measures that CERAD developed during its first decade and their continued use in their original and translated forms. These measures include clinical, neuropsychological, neuropathologic, and behavioral assessments of AD and also assessment of family history and parkinsonism in AD. An approach to evaluating neuroimages did not meet the standards desired. Further evaluations that could not be completed because of lack of funding (but where some materials are available) include evaluation of very severe AD and of service use and need by patient and caregiver. The information that was developed in the U.S. and abroad permits standardized assessment of AD in clinical practice, facilitates epidemiologic studies, and provides information valuable for individual and public health planning. CERAD materials and data remain available for those wishing to use them.
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Neuropsychological deficits have been documented in patients with obstructive sleep apnea syndrome (OSAS). Both nocturnal hypoxemia and impairement of daytime vigilance have been suggested as the pathogenesis of these deficits, yet it remains difficult to find good correlations between cognitive deficits and either of these physiological parameters. In the present study, 10 normal controls were compared to 10 moderately and 10 severely apneic patients, all recorded in a sleep laboratory for two consecutive nights, with a vigilance and neuropsychological assessment made during the intervening day. Relative to the controls, moderate and severe OSAS showed differences in many cognitive functions, although the severely affected showed the greater differences. Moreover, severe apneics were also worse than moderate apneics on tests that were found to be normal in the latter group. This suggests a discontinuity in the appearance of neuropsychological deficits as OSAS progresses. Further analyses revealed that reductions in general intellectual measures, as well as in executive and psychomotor tasks were all attributable to the severity of hypoxemia, while other attention and memory deficits were related to vigiance impairment. Therefore, both vigilance impairment and nocturnal hypoxemia may differentially contribute to the cognitive dysfunctions found in OSAS.