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Short sleep duration and poor sleep continuity have been implicated in the susceptibility to infectious illness. However, prior research has relied on subjective measures of sleep, which are subject to recall bias. The aim of this study was to determine whether sleep, measured behaviorally using wrist actigraphy, predicted cold incidence following experimental viral exposure. A total of 164 healthy men and women (age range, 18 to 55 y) volunteered for this study. Wrist actigraphy and sleep diaries assessed sleep duration and sleep continuity over 7 consecutive days. Participants were then quarantined and administered nasal drops containing the rhinovirus, and monitored over 5 days for the development of a clinical cold (defined by infection in the presence of objective signs of illness). Logistic regression analysis revealed that actigraphy- assessed shorter sleep duration was associated with an increased likelihood of development of a clinical cold. Specifically, those sleeping <5 h (odds ratio [OR]= 4.50, 95% confidence interval [CI], 1.08-18.69) or sleeping between 5 to 6 h (OR = 4.24, 95% CI, 1.08-16.71) were at greater risk of developing the cold compared to those sleeping >7 h per night; those sleeping 6.01 to 7 h were at no greater risk (OR = 1.66; 95% CI 0.40-6.95). This association was independent of prechallenge antibody levels, demographics, season of the year, body mass index, psychological variables, and health practices. Sleep fragmentation was unrelated to cold susceptibility. Other sleep variables obtained using diary and actigraphy were not strong predictors of cold susceptibility. Shorter sleep duration, measured behaviorally using actigraphy prior to viral exposure, was associated with increased susceptibility to the common cold. Copyright © 2015 Associated Professional Sleep Societies, LLC. All rights reserved.
SLEEP, Vol. 38, No. 9, 2015 1353 Sleep and the Common Cold—Prather et al.
Growing evidence demonstrates that short sleep duration
(< 6 or 7 h/night) and poor sleep continuity are associated with
the onset and development of a number of chronic illnesses,1–4
susceptibility to acute infectious illness,5 –7 and premature
mo r talit y.8 –11 Experimental evidence in animals and humans
suggests that the immune system serves as a key biological
pa t h way.12 –14 For instance, total and partial sleep deprivation in
humans results in modulation of immune parameters critical
to host resistance, including diminished T cell proliferation,15
shifts in T helper cell cytokine responses,16,17 decreases in nat-
ural killer (NK) cell cytotoxicity,18,1 9 and increased activation
of proinammatory pathways.20–23
Sleep related modulation of the immune system is also ob-
served when sleep is measured in the natural environment,
with implications for clinical outcomes.6,24 We recently re-
ported that short sleep duration and poor sleep continuity, mea-
sured by sleep diary over 14 consecutive days, predicted the
incidence of developing a biologically veried cold following
viral exposure.6 One of the limitations of this prior study was
Study Objectives: Short sleep duration and poor sleep continuity have been implicated in the susceptibility to infectious illness. However, prior
research has relied on subjective measures of sleep, which are subject to recall bias. The aim of this study was to determine whether sleep,
measured behaviorally using wrist actigraphy, predicted cold incidence following experimental viral exposure.
Design, Measurements, and Results: A total of 164 healthy men and women (age range, 18 to 55 y) volunteered for this study. Wrist
actigraphy and sleep diaries assessed sleep duration and sleep continuity over 7 consecutive days. Participants were then quarantined and
administered nasal drops containing the rhinovirus, and monitored over 5 days for the development of a clinical cold (dened by infection in the
presence of objective signs of illness). Logistic regression analysis revealed that actigraphy- assessed shorter sleep duration was associated
with an increased likelihood of development of a clinical cold. Specically, those sleeping < 5 h (odds ratio [OR] = 4.50, 95% condence inter val
[CI], 1.08–18.69) or sleeping between 5 to 6 h (OR = 4.24, 95% CI, 1.08–16.71) were at greater risk of developing the cold compared to those
sleeping > 7 h per night; those sleeping 6.01 to 7 h were at no greater risk (OR = 1.66; 95% CI 0.40–6.95). This association was independent
of prechallenge antibody levels, demographics, season of the year, body mass index, psychological variables, and health practices. Sleep
fragmentation was unrelated to cold susceptibility. Other sleep variables obtained using diary and actigraphy were not strong predictors of cold
Conclusions: Shorter sleep duration, measured behaviorally using actigraphy prior to viral exposure, was associated with increased susceptibility
to the common cold.
Keywords: common cold, immunity, rhinovirus, sleep continuity, sleep duration
Citation: Prather AA, Janicki-Deverts D, Hall MH, Cohen S. Behaviorally assessed sleep and susceptibility to the common cold. SLEEP
Behaviorally Assessed Sleep and Susceptibility to the Common Cold
Aric A. Prather, PhD1; Denise Janicki-Deverts, PhD2; Martica H. Hall, PhD3; Sheldon Cohen, PhD2
1Department of Psychiatr y, University of California, San Francisco, CA; 2Department of Psychology, Carnegie Mellon University, Pittsburgh, PA;
3Depart ment of Psychiatr y, Universit y of Pittsburgh Medical Center, Pittsburgh, PA
pii: sp-00619-14
a reliance on self-reported sleep, which is subject to recall
bias leading to inaccurate sleep estimates. Indeed, individuals
often overestimate duration and underestimate minutes awake
across the night.25 Whether objectively measured sleep indices
represent signicant predictors of acute infectious illness fol-
lowing viral exposure remains unknown.
To address this gap in the literature, the current study mea-
sured sleep behavior objectively using wrist actigraphy and
subjectively using sleep diaries over 7 consecutive days and
investigated whether measures of sleep duration and continuity
predicted susceptibility to the common cold in participants
subsequently exposed to a virus (rhinovirus) that causes the
common cold. Following exposure to the cold virus, partici-
pants were quarantined and monitored for cold symptoms and
development of clinical illness. We hypothesized that shorter
sleep duration and poorer sleep continuity would be associated
with increased incidence of a biologically veried cold and that
these associations would be independent of sociodemographic,
psychological, and behavioral factors previously shown to pre-
dict cold incidence using this paradigm.6, 7,26 28
Data were collected between 2007 and 2011. Study par-
ticipants for these analyses included 94 men and 70 women,
aged between 18 and 55 y (mean age = 29.9, standard devia-
tion [SD] = 10.9) from the Pittsburgh, Pennsylvania metro-
politan area who responded to study advertisements and
were judged to be in good health. Volunteers were excluded
if they had a history of nasal surgery or any other chronic ill-
ness (e.g., asthma, coronary heart disease, or obstructive sleep
A commentary on this article appears in this issue on page 1341.
Submitted for publication October, 2014
Submitted in nal revised form December, 2014
Accepted for publication January, 2015
Address correspondence to: Aric A. Prather, PhD, Center for Health and
Community, Department of Psychiatry, University of California, San Fran-
cisco, CA; Email: or Sheldon Cohen, PhD, Depar t-
ment of Psychology, Carnegie Mellon University, Pittsburgh, PA; Email:
SLEEP, Vol. 38, No. 9, 2015 1354 Sleep and the Common Cold—Prather et al.
apnea); abnormal ndings based on urinalysis, complete blood
count, or blood enzyme levels; were pregnant or currently lac-
tating; were positive for the human immunodeciency virus;
or taking medications regularly, including sleep medications
and oral contraceptives. They were also excluded if they had
been hospitalized in the past 5 y or were currently taking medi-
cations for psychiatric conditions. In order to maximize the
rate of infection by the virus, specic levels of serum antibody
to the challenge virus were obtained at screening and partici-
pants were excluded with titers higher than 4. Each participant
was paid $1,000 for their participation at the conclusion of the
study. This study received institutional review board approval,
and written, informed consent was obtained for each study
Volunteers presenting for possible enrollment underwent
medical screening, including a blood draw to assess specic
serum neutralizing antibody titer for rhinovirus 39 (RV39).
Qualifying participants were enrolled and during the approxi-
mately 2 mo that preceded viral challenge they completed
questionnaire batteries, 2 w of daily interviews to assess posi-
tive emotions, and a subsequent 1 w of wrist actigraphy and
concurrent sleep diary to objectively and subjectively measure
sleep behavior. Another sample of blood was collected to as-
sess antibody level just before (3–5 days) viral exposure, which
provided an estimate of prechallenge antibody titers.
Participants were then isolated in a local hotel for a 6-day
period. During the rst 24 h of the quarantine, prior to viral ex-
posure, participants underwent a nasal examination and nasal
lavage; baseline nasal mucociliary and nasal mucus production
were assessed at this time. Those showing signs or symptoms
of a cold on this day were dismissed. Then, participants re-
ceived nasal drops containing approximately 150 tissue cul-
ture infectious dose (TCID50)/mL of RV39. Volunteers were
subsequently quarantined for 5 days. On each day, nasal la-
vage samples were collected to assess infection (virus culture).
Additionally, daily nasal mucociliary clearance function and
nasal mucus production were assessed as objective markers of
illness. Approximately 28 days after viral exposure, blood was
collected for serological testing.
Sleep Measures
Participants wore an Actiwatch-(64) (Philips Respironics
Inc, McMurray, PA) on their nondominant wrists for 7 con-
secutive nights. Data were stored in 1-min epochs and vali-
dated software algorithms (Philips Respironics Inc) were
used to estimate sleep parameters. The two actigraphy vari-
ables included in these analyses were total sleep time and
fragmentation index. Total sleep time, which was used to
estimate sleep duration, was dened as the total amount of
minutes scored as sleep by the software algorithm in a given
dened sleep interval. Fragmentation index is a measure of
restlessness during sleep as measured by sleep epochs as-
sociated with movement (range 0 to 150, with higher values
indicating poorer sleep continuity). As expected, actigraphy-
assessed sleep efciency, dened as the percentage of the
sleep interval scored as sleep, was inversely correlated with
fragmentation index in this sample (r = −0.59, P < 0.001). We
chose fragmentation index instead of sleep efciency given
the documented poor specicity associated with actigraphy-
assessed sleep efciency.29
Self-report sleep diaries were obtained concurrently with
actigraphy collection. Each morning, participants reported in
their sleep diary what time they went to sleep, what time they
woke up, and the min it took to fall asleep. Sleep time was
calculated as the time a participant reported waking up minus
the time the participant went to sleep. Self-reported sleep dura-
tion was computed by sleep time minus the minutes required
to fall asleep. Sleep efciency was calculated as sleep duration
divided by sleep time multiplied by 100. Actigraphy and diary
estimates for sleep (actigraphy: sleep duration and fragmen-
tation; sleep diary: sleep duration and sleep efciency) were
obtained by averaging over the collection period for all partici-
pants with data for at least 5 of the 7 days.
Control Variables
We controlled for a number of covariates previously asso-
ciated with susceptibility to the common cold, including pre-
challenge viral-specic antibody levels to RV; age; sex; race;
body mass index (BMI); the season in which the trial occurred;
years of education; household income, health habits including
current smoking status, physical activity, and alcohol con-
sumption; and psychological variables including perceived
socioeconomic status, perceived stress, extraversion, agree-
ableness, and positive emotional style. These covariates were
assessed either during eligibility screening or in the interval
between screening and the viral challenge.
Participants self-reported their age, sex, and race. They de-
scribed their primary racial and ethnic group by choosing from
six categories (white, Caucasian; black, African American;
Native American, Eskimo, Aleut; Asian or Pacic Islander;
Hispanic, Latino; Other). For the analyses, the racial or ethnic
groups were dummy coded, with all but whites and blacks col-
lapsed into a single “other” category. BMI (weight in kg/height
in m2) was computed based on measurements of participants’
weight and height.
Income was assessed by having participants endorse one of
13 household income categories (before taxes) that best repre-
sented them. These categories ranged from less than $5,000 to
$150,000 or more; income was dened as the median income
for the identied category and treated as a continuous vari-
able. Participants’ education was assessed by asking them to
report on their highest educational attainment. Nine response
items were provided, ranging from “didn’t nish high school”
to “doctoral degree.” Answers were converted into number of
years of education based on their responses (e.g., high school,
12 y; PhD, 20 y). Perceived socioeconomic rank was assessed
by participants placing themselves on a nine-rung of a ladder
in terms of where they stand in their country based on income,
education, and occupation.26
Health habits were obtained through self-report question-
naires. Participants were deemed current smokers if they an-
swered “yes” to being asked whether they currently smoked
cigarettes, cigars, or pipes on a daily basis. Physical activity
was assessed by asking participants whether they engaged in
regular activity at least once per week (1, yes; 0, no). Alcohol
consumption was obtained by asking participants the average
SLEEP, Vol. 38, No. 9, 2015 1355 Sleep and the Common Cold—Prather et al.
number of drinks they consumed per day (one drink = one
glass of wine, 12 oz of beer, or one shot of hard liquor).
Psychological variables that were assessed by questionnaire
included a 10-item perception of stress over the past month30;
extraversion and agreeableness were assessed using the 10-
item versions from the International Personality Item Pool
(IPIP) Big Five Factor Markers.31 Finally, positive emotional
style was measured as part of an evening interview assessment
that was conducted over 14 consecutive days. During each
of the 14 daily interviews participants reported the extent to
which they felt happy, calm, lively, full of pep, and cheerful
throughout the preceding day; ratings for each item were av-
eraged to create a daily total positive affect score across the
interview period.27
Virus Culture and Antibody Response
Virus-specic neutralizing antibody titers were measured
in serum samples obtained before and approximately 28 days
after viral exposure. The results were expressed as reciprocals
of the nal dilution of serum.32 Daily nasal lavage samples
were frozen at −80°C and later cultured for RV using standard
Signs of Illness
Daily mucus production was obtained by collecting used tis-
sues in sealed plastic bags.33 The bags were weighed and the
weights of the tissues and bags were subtracted. Nasal muco-
ciliary clearance function was measured by administering a
dye into the anterior area of the nose and calculating the time
taken for the dye to reach the nasopharynx.33
Clinical Cold Criteria
Study participants were considered to have a clinical cold
if they were both infected and met illness criteria. Infection
was dened as the recovery of the challenge virus on any of
the postchallenge days or a fourfold or greater increase in the
virus-specic serum neutralizing antibody titer measured pre-
exposure to 28 days post-exposure.33 Illness criterion for an
objective cold required a total adjusted mucus weight of ≥ 10 g
or a total adjusted nasal clearance time of ≥ 35 min.7
Statistical Analysis
All analyses were carried out using SPSS version 22 (SPSS
Inc., Chicago, IL). Data were drawn from 212 volunteers who
participated in this study. Of those, actigraphy measures were
collected from 165 participants. One participant was identi-
ed as a clear outlier (> 9 standard deviations above the mean
on sleep duration) and excluded, yielding 164 participants for
these analyses. Self-report sleep measures obtained by sleep
diary were available on 159 participants. Income, BMI, and al-
cohol consumption were log (base-10) transformed to better ap-
proximate a normal distribution. Logistic regression was used
to predict colds (1, yes; 0, no). Sleep measures were treated as
continuous variables with the exception of self-reported sleep
efciency, which was negatively skewed, and was modeled as
a categorical (quartile) predictor. We reported regression coef-
cients with standard errors and probability values.
Age and prechallenge viral-specic antibody titers were
included as covariates in all analyses. Next, we conducted a
series of regressions entering one of the 14 separate covari-
ates, along with age and prechallenge antibody titers. The
approach reduces the risks of “overtting” the regression
models34,35; however, we also computed single models that
included all study covariates simultaneously. In addition, to
better elucidate the independent and interactive contributions
of duration and continuity measures on cold susceptibility,
we t models that included both actigraphy assessed sleep
duration and fragmentation simultaneously as predictors as
well as tested the interaction between them (sleep duration ×
Finally, to better clarify associations between actigraphy as-
sessed sleep duration and cold incidence and to provide an esti-
mate effect size, sleep duration was categorized based on hours
of sleep (< 5 h, n = 36; 5 to 6 h, n = 54; 6.01 to 7 h, n = 52; > 7 h,
n = 22). We tted a logistic regression using this categorical
sleep variable and reported odds ratios (OR) with 95% con-
dence intervals (CIs).
Tab le 1 —Sample characteristics (n = 164).
Variable Mean (SD) or % (n)
Age 29.9 (10.9)
Sex (% female) 42.7 (70)
Body mass index (kg/m2)27.4 (6.5)
Race (%)
White/Caucasian 68.3 (112)
Black/African American 26.2 (43)
Other 5.5 (9)
Prechallenge antibodies (titer) 2.45 (2.8)
Season (%)
Winter 26.2 (43)
Spring 31.7 (52)
Summer 42.1 (69)
Fall 0 (0)
Education (y) 14.1 (1.9)
Income ($) 21,856 (23,202)
Subjective SES 4.2 (1.8)
Health practices
Smoking status (% current smoker) 32.9 (54)
Physical activity (% engage in regular
84.8 (139)
Alcohol consumption (# of drinks/w) 2.5 (4.8)
Psychological measures
Perceived stress scale 12.3 (5.8)
Agreeableness 38.9 (6.1)
Extraversion 32.5 (7.0)
Positive emotional style 14.3 (4.3)
Sleep measures
Sleep diary
Sleep duration (h) 7.5 (1.2)
Sleep efciency (%) 96.1 (3.6)
Sleep duration (h) 5.8 (1.1)
Fragmentation index (% fragmented) 33.3 (13.4)
SD, standard deviation; SES, socioeconomic status.
SLEEP, Vol. 38, No. 9, 2015 1356 Sleep and the Common Cold—Prather et al.
Sample Characteristics and Sleep Scores
Table 1 presents descriptive data for all variables involved
in the analyses. Of the 164 participants, 124 (75.6%) were in-
fected and 48 (29.3%) developed a biologically veried cold,
which was dened as infection and objective cold criterion.
As expected, sleep measures were intercorrelated (actig-
raphy sleep duration and fragmentation, r = −0.37, P < 0.001;
actigraphy sleep duration and self-reported sleep duration,
r = 0.49, P < 0.001; actigraphy sleep duration and self-reported
sleep efciency, r = 0.27, P < 0.001; actigraphy fragmentation
and self-reported sleep efciency, r = −0.12, P = 0.14).
Sleep and Susceptibility to the Common Cold
Adjusting for age and prechallenge antibody titers, shorter
sleep duration, assessed using actigraphy, was associated with
increased risk for the development of the cold (b = −0.44, stan-
dard error [SE] = 0.17, P = 0.011). In contrast, sleep fragmen-
tation and self-reported sleep duration were not signicant
predictors of cold susceptibility (fragmentation: b = −0.01,
SE = 0.01, P = 0.715; self-reported sleep duration: b = −0.15,
SE = 0.16, P = 0.325). Similarly, participants reporting sleep ef-
ciency in the bottom quartile were no more likely to develop
the cold than individuals in the top quartile (b = 0.57, SE = 0.51,
P = 0.258).
To follow up on the signicant association between actig-
raphy-assessed sleep duration and the likelihood of developing
a biologically veried cold, additional models were computed
adjusting for study covariates. Here, we carried out a set of
regressions that entered each covariate one by one in separate
models (14 separate models). As displayed in Table 2, shorter
sleep duration continued to be associated with increased rates
of developing a cold (all Ps < 0.015). Furthermore, shorter
sleep duration predicted increased odds of developing a cold
when all covariates were included in a single model (b = −0.49,
SE = 0.2 0, P = 0.012). Sle ep fr agment a t ion wa s not signica n tly
related to cold incidence when all covariates were included in a
single model (b = −0.01, SE = 0.02, P = 0.755). This was simi-
larly the case for self-reported sleep duration and efciency
(data not shown).
To better characterize the effect of sleep duration on odds of
developing a cold, sleep categories were created. As illustrated
Tab le 2 Logistic regression models with actigraphy-based sleep
duration predicting incidence of the cold, adjusting for each study
covariate separately.
Modelab (SE) P
Male −0.44 (0.37) 0.232
Female Reference
Sleep duration −0.44 (0.17) 0.011
Body mass indexb2.79 (2.01) 0.166
Sleep duration −0.43 (0.17) 0.012
White −0.36 (0.75) 0.629
Black 0.24 (0.79) 0.766
Other Reference
Sleep duration −0.43 (0.17) 0.014
Season of trial
Winter 0.13 (0.42) 0.756
Spring −1.12 (0.49) 0.022
Summer Reference
Sleep duration −0.46 (0.18) 0.010
Education 0.00 (0.09) 0.985
Sleep duration −0.44 (0.17) 0.011
Incomeb0.04 (0.41) 0.926
Sleep duration −0.43 (0.17) 0.013
Subjective SES 0.05 (0.10) 0.602
Sleep duration −0.45 (0.17) 0.010
Current smoker
No −0.64 (0.39) 0.100
Yes Reference
Sleep duration −0.44 (0.17) 0.012
Regular physical activity
No −0.20 (0.54) 0.703
Yes Reference
Sleep duration −0.44 (0.17) 0.011
Alcohol consumptionb0.76 (0.41) 0.065
Sleep duration −0.44 (0.18) 0.013
Perceived stress 0.00 (0.03) 0.943
Sleep duration −0.44 (0.17) 0.011
Agreeableness 0.02 (0.03) 0.559
Sleep duration −0.45 (0.17) 0.011
Extraversion 0.05 (0.03) 0.066
Sleep duration −0.47 (0.18) 0.008
Positive emotional style 0.01 (0.05) 0.793
Sleep duration −0.44 (0.17) 0.012
Sleep duration (full model)c−0.49 (0.20) 0.012
aAll models adjusted for age and prechallenge antibodies. bLog-
10 transformed. cModel included all covariates. SE, standard error;
SES, socioeconomic status.
Figure 1—Sleep duration (measured by wrist actigraphy) averaged over
a 7-day period before virus exposure is associated with percentage of
participants who subsequently developed a cold. The percentage of
colds is based on predicted values (adjusted for age and prechallenge
viral-specic antibody levels).
< 5 5– 6 6.01–7 > 7
Adjusted % with Objective Colds
Actigraphy Sleep Duration (hours)
SLEEP, Vol. 38, No. 9, 2015 1357 Sleep and the Common Cold—Prather et al.
in Figure 1, the predictive inuence of sleep duration on cold
susceptibility indicates a threshold effect at 6 or fewer hours of
sleep (< 5 h, OR = 4.50; 95% CI 1.08–18.69; 5–6 h, OR = 4.24;
95% CI 1.08 –16.71; 6.01–7 h, OR = 1.66; 95% CI 0.406.95; > 7
h, 1 [reference]).
The observed elevated risk of developing the cold in partici-
pants experiencing shorter sleep duration may have been due
to increased susceptibility to infection and/or increased illness
expression among those infected. In this regard, in adjusted
analyses, actigraphy assessed sleep duration was unrelated to
rates of infection (b = −0.11, SE = 0.17, P = 0.543). Similarly,
among those who were infected (n = 124), shorter sleep dura-
tion was not signicantly related to increased odds of meeting
illness criteria for mucus production or nasal clearance time
(b = −0.32, SE = 0.19, P = 0.090). Although there were no sig-
nicant relationships of actigraphy-assessed sleep duration
with either infection or expression of illness, the association
with cold incidence appears to be primarily driven by illness
Because measures of actigraphy assessed sleep duration
and fragmentation capture different aspects of an individual’s
sleep, we tested whether the effects of duration operated inde-
pendent of fragmentation in predicting risk for a biologically
veried cold. To this end, we t a regression model with both
measures entered together. Analyses revealed that sleep dura-
tion continued to predict cold incidence adjusting for age and
prechallenge antibody levels (b = −0.53, SE = 0.19, P = 0.005)
as well as in the fully adjusted (16 covariates and fragmenta-
tion) model (b = −0.56, SE = 0.21, P = 0.006). There was no
evidence that sleep duration and fragmentation interacted to
predict cold incidence (P = 0.92).
Shorter sleep duration, measured by wrist actigraphy over
a 7-day period, was prospectively associated with increased
incidence of the common cold following experimental viral
challenge. This association was independent of a cadre of co-
variates, including age, prechallenge antibody levels, sex, body
mass index, race, season of trial, income, education, perceived
socioeconomic status, smoking, physical activity, alcohol con-
sumption, perceived stress, agreeableness, extraversion, and
positive emotional style. This study provides the rst prospec-
tive evidence that behaviorally assessed sleep duration serves
as a predictor of cold susceptibility.
Analyses revealed a linear association between sleep dura-
tion and cold susceptibility; however, when categorized based
on hours of sleep, a threshold effect was observed such that in-
dividuals sleeping fewer than 6 h of sleep per night were at ele-
vated risk whereas those sleeping more than 6 h were not. This
is consistent with some epidemiologic evidence that nd strong
effects on morbidity and mortality in short sleepers compared
to normal sleepers.1,11,36 For instance, Patel and colleagues
found that in a sample of nearly 57,000 women, those who re-
ported sleeping 6 h per night were at signicantly greater
risk of developing pneumonia compared to those sleeping 8 h
per night.5 Those sleeping 7 h were at no greater risk than 8-h
sleepers. Emerging evidence also suggests that long sleepers
(≥ 9 h per night) are at increased risk of disease.10,11, 37 The un-
derlying mechanisms linking negative health and long sleep
are poorly understood38–40 ; however, depression and medical
comorbidities have been implicated.38 Very few participants in
this study reported sleeping more than 9 h per night (11.3% by
sleep diary, 0.6% by actigraphy), making it difcult to deter-
mine whether long sleep was a risk factor of cold incidence.
The small sample of long sleepers in this study may be due to
the fact that the study sample was carefully screened to meet
good health standards, including being free from psychiatric
Self-reported diary measures of duration and sleep ef-
ciency were unrelated to cold incidence. This is in contrast
to our prior work that found that poorer sleep efciency and
shorter sleep duration, measured via a 14-day daily interview,
predicted cold susceptibility.6 There are several possible ex-
planations for differences across studies. First, fewer partici-
pants became infected in this sample, which may have limited
our power to detect effects using self-report measures. Second,
this study relied on a shorter 7-day sleep diary rather than a
14-day daily interview, which may have produced less stable
averages as well as less accurate estimates of sleep. In regard
to sleep estimates, employment of a daily interview in the prior
study helped ensure timely assessments of self-reported sleep,
which potentially decreased recall bias. Third, given that ac-
tigraphy has been well correlated with polysomnography,41
the gold standard of measurement in sleep research, it is also
possible that had our prior study included actigraphy assess-
ment concurrently with the daily interview sleep data, those
ndings would have been even more robust. Future studies
incorporating both actigraphy and sleep diaries are needed to
understand when and why certain sleep measures signicantly
predict immune function.
What are the mechanisms that might link sleep and suscep-
tibility to acute infectious illness? Sleep, along with circadian
rhythms, exerts substantial regulatory effects on the immune
system.42,43 Circulating immune cells, including T and B cells,
peak early in the night and then decline throughout the noc-
turnal hours moving out of circulation into lymphoid organs
where exposure to virally infected cells occur.43– 45 Studies
employing experimental sleep loss also support functional
changes relevant to host resistance. Sleep deprivation results
in down regulation in T cell production of interleukin-219,44 and
a shift away from T-helper 1 responses, marked by a reduc-
tion in the ratio of interferon-γ/IL-4 production.16 Sleep loss
is associated with diminished proliferative capacity of T cells
in vitro15 as well as modulation of the function of antigen pre-
senting cells critical to virus uptake.46
Illness expression in colds is generally attributed to blunted
downregulation of local inammatory responses.47,4 8 Emerging
evidence demonstrates bidirectional links between sleep and
inammation.14,42,49 Proinammatory activity has a role in the
homeostatic regulation of sleep.50, 51 Likewise, some but not
all studies that employ partial and total sleep restriction nd
substantial increases in systemic levels of proinammatory
cytokines52 as well as enhanced inammatory gene expres-
sion and transcriptional pathways that support inammatory
processes.20 ,21 In addition, recent evidence suggests that el-
evated systemic inammation mediates prospective associa-
tions between short sleep duration and premature mortality.53
Future studies characterizing the immunologic mediators of
SLEEP, Vol. 38, No. 9, 2015 1358 Sleep and the Common Cold—Prather et al.
cold incidence in the context of sleep duration and our viral
challenge paradigm are needed to clarify when in the infection
process sleep has the most potent effects.
Like prior work, we nd that infectious risk is strongest in
the shortest of sleepers, suggesting that “normal” sleepers (e.g.,
7 to 9 h per night for adults) would be protected in this context.
Whether sleep interventions aimed at increasing sleep dura-
tion would protect individuals from cold incidence remains
an open question. In this regard, recent ndings that cognitive
behavioral therapy for older adults with insomnia resulted in
decreased levels of systemic inammation54 raises the possi-
bility that a similar enhancement in cell-mediated immunity
could also be observed. Given that infectious illness (i.e., inu-
enza and pneumonia) remains one of the top 10 leading causes
of death in the United States,55 the current data suggest that a
greater focus on sleep duration, as well as sleep health more
br oadly, 56 is indicated.
In summary, these novel ndings provide the rst evidence
that sleep duration assessed behaviorally through actigraphy
predicts incidence of infectious illness using an experimental
viral challenge. Although this study does not provide direct
evidence of causality, the prospective nature of the viral chal-
lenge design does eliminate concerns of reverse causation. It
is recognized that actigraphy is a behavioral measure of rest/
activity patterns and is not an objective measure of sleep per
se. Although actigraphy has been shown to correlate well with
polysomnography in healthy samples,41 actigraphy-assessed
indices of sleep duration cannot identify specic dimensions of
sleep (e.g., decreased slow wave sleep) that may be contributing
to infectious risk. In addition, future studies investigating the
immunologic mechanisms underlying these effects as well as
generalizability of these ndings to other samples (i.e., older
adults; sleep disordered patients) are warranted.
This was not an industry supported study. Preparation of
this paper was supported by the National Center for Comple-
mentary and Alternative Medicine (AT006694), and data col-
lection by the National Institute of Allergy and Infectious
Diseases (AI066367). Clinical and regulatory assistance for the
study was provided by National Institute of Health grants (UL1
RR024153 and UL1 TR000005) to the University of Pittsburgh
Clinical and Translational Science Institute. Dr. Prather’s par-
ticipation was supported by a grant from the National Heart,
Lung, & Blood Institute (K08HL112961). The authors have in-
dicated no nancial conicts of interest.
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... 10 After an experimental rhinovirus challenge, individuals sleeping ≤6 h are at greater risk of developing the cold. 11 Moreover, a systemic review demonstrated that individuals sleeping less than 7 h are more prone to have upper airway respiratory tract infections. 12 A link between sleep duration and increased COVID-19 susceptibility is shown using multivariable Mendelian randomization. ...
... 21 A cutoff of 6 h of sleep has been shown to be associated with significant morbidity and mortality. 11,22,23 Thus, we categorized the patients into two groups: <6 h (n=77) and ≥6 hours (n=193). Demographic characteristics of the patients are shown in Table 1. ...
Purpose: Sleep disturbance has been implicated in poor prognosis of coronavirus disease 2019 (COVID-19), but less is known about the influence of short sleep duration on COVID-19 outcomes. We aim to investigate whether short sleep duration is associated with prolonged virus shedding duration in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron-infected patients. Patients and methods: A total of 270 patients with a laboratory confirmed COVID-19 diagnosis during SARS-CoV-2 Omicron-predominant period were recruited. Self-reported sleep duration of the patients was collected. The two-way analysis of variance (ANOVA) was used to determine the interactions between sleep duration and variables, and multivariate logistic regression analysis was used to analyze the effect of independent variables on longer virus shedding duration. Results: The two-way ANOVA revealed a significant sleep duration × snoring interaction effect for virus shedding duration, and a sleep duration × sex interaction effect for virus shedding duration. Multivariate logistic regression model illustrated that patients sleeping <6 h were at greater risk of prolonged virus shedding duration compared to those sleeping ≥6 hours (OR = 1.80, 95% CI = 1.01-3.26), independent of age, sex, co-existing diseases, vaccination condition, and antiviral treatment. Conclusion: Short sleep duration (<6 h) was associated with increased virus shedding in SARS-CoV-2 Omicron-infected patients.
... Over 40% of athletes in one study demonstrated low quantity of sleep and/or the quality of their sleep was poor (Mah et al., 2018). Chronically restricted sleep has important implications for potential injury (Luke et al., 2011), susceptibility to infectious illness (Prather et al., 2015), and the accuracy of concussion assessment (Silverberg et al., 2016). Additionally, restricted sleep has been shown to reduce reaction times (Dinges et al., 1997) and impair sport execution (Reyner and Horne, 2013), which both may have a negative impact on the athletes' performance and, subsequently, their overall mental health. ...
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Introduction There is a need to psychometrically develop assessment instruments capable of screening mental health disorders in athlete populations. The current study was conducted to determine reliability, validity and clinical utility of the Mental Health Disorders Screening Instrument for Athletes (MHDSIA). Methods and results 259 collegiate athletes completed the MHDSIA. Factor analysis determined a single factor with good internal consistency, and this factor was positively correlated with an established measure of psychiatric symptomology (Symptom Checklist 90-R), demonstrating its concurrent validity. An optimum clinical cutoff score (i.e., 32) was determined using Receiver Operating Characteristic (ROC) analyses to assist appropriate mental health referrals. Discussion Results suggest the MHSIA is a reliable, valid, and relatively quick and easy to interpret screen for the broad spectrum of mental health disorders in collegiate athletes. As expected, NCAA athletes reported lower MHDSIA scores than club and intramural athletes, while males reported similar severity scores as females.
... Insu cient sleep has detrimental health effects. Sleep disturbances, particularly short sleep intervals, are common among hypothyroid patients [22]. Short sleep duration and poor sleep quality could be hypothyroidism risk factors or causes [23]. ...
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Background: While the link between hypothyroidism and disturbed sleep patterns has been recognized, the available data are inconsistent, making it difficult to establish causality. This study aimed to investigate the causal relationship between certain sleep traits and hypothyroidism. Methods: Using publicly available genomewide association study (GWAS) data, we applied linkage disequilibrium score regression (LDSC) to identify genetic associations between hypothyroidism and various sleep traits. Two-sample Mendelian randomization (MR) analysis was then conducted to assess the causal relationship between aberrant sleep features and the risk of hypothyroidism. The IVW, MR-Egger regression, weighted median, and weighted mode methods were used. To detect level polymorphism and outliers, MR-Egger regression and MR-PRESSO methods were employed. Results: A genetic association between hypothyroidism and nap during the day and getting up in morning (rg=-0.0982, p=0.0007; rg=-0.101, p=0.0001). In addition, a causal relationship between hypothyroidism and sleep duration (IVW, OR 1.5208, 95%CI: 0.1082-0.7304, P=0.0082) and getting up in morning (IVW, OR 1.8375, 95%CI: 0.3717-0.8452, P=4.73×10⁻⁷). Furthermore, the reverse MR analysis did not reveal any causal link between hypothyroidism and aberrant sleep traits. Conclusion: MR analysis demonstrated a causal link between hypothyroidism and certain aberrant sleep traits. Sleep duration should be considered as a potential factor in disease models for improving sleep quality and reducing the risk of hypothyroidism.
... Just as sickness affects sleep patterns, short sleep can also increase susceptibility to sickness (Prather et al., 2015). This relationship appears to be mediated by cytokine activity, including TNF-a and interleukin-6 (IL-6). ...
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This study aimed to examine the joint association of daily rest period (DRP) and sleep duration with occupational stress and sickness absence in Japanese daytime employees. This study utilized a web-based cross-sectional survey conducted in February 2022. The 13,306 participants reported their DRPs and sleep duration. Occupational stress was assessed using the New Brief Job Stress Questionnaire, while the frequency of sickness absence was measured using a 4-point Likert scale. The participants were categorized into 14 groups based on their DRPs and sleep duration. Logistic regression analyses revealed that the combination of a short DRP and normal sleep duration, as well as the combination of an adequate DRP and short sleep duration, were significantly associated with high occupational stress compared to the reference group (adequate DRP and normal sleep duration). These results indicate that not only normal sleep duration but also sufficient DRPs are important for reducing occupational stress. However, only the combination of a short DRP and normal sleep duration, and not the combination of an adequate DRP and short sleep duration, were significantly associated with a lower frequency of sickness absence. This may be owing to the possibility that employees with a short DRP (indicating longer working hours) are too busy to take leave even when they are sick.
Background: Sleep disturbances, as manifested in insomnia symptoms of difficulties falling asleep or frequent nighttime awakenings, are a strong risk factor for a diverse range of diseases involving immunopathology. Low-grade systemic inflammation has been frequently found associated with sleep disturbances and may mechanistically contribute to increased disease risk. Effects of sleep disturbances on inflammation have been observed to be long lasting and remain after recovery sleep has been obtained, suggesting that sleep disturbances may not only affect inflammatory mediators, but also the so-called specialized pro-resolving mediators (SPMs) that actively resolve inflammation. The goal of this investigation was to test for the first time whether the omega-3 fatty acid-derived D- (RvD) and E-series (RvE) resolvins are impacted by prolonged experimental sleep disturbance (ESD). Methods: Twenty-four healthy participants (12F, age 20-42 years) underwent two 19-day in-hospital protocols (ESD/control), separated by >2 months. The ESD protocol consisted of repeated nights of short and disrupted sleep with intermittent nights of undisturbed sleep, followed by three nights of recovery sleep at the end of the protocol. Under the control sleep condition, participants had an undisturbed sleep opportunity of 8 hours/night throughout the protocol. The D- and E-series resolvins were measured in plasma using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Results: The precursor of the D-series resolvins, 17-HDHA, was downregulated in the ESD compared to the control sleep condition (p<.001 for condition), and this effect remained after the third night of recovery sleep has been obtained. This effect was also observed for the resolvins RvD3, RvD4, and RvD5 (p<.001 for condition), while RvD1 was higher in the ESD compared to the control sleep condition (p<.01 for condition) and RvD2 showed a mixed effect of a decrease during disturbed sleep followed by an increase during recovery sleep in the ESD condition (p<.001 for condition*day interaction). The precursor of E-series resolvins, 18-HEPE, was downregulated in the ESD compared to the control sleep condition (p<.01 for condition) and remained low after recovery sleep has been obtained. This effect of downregulation was also observed for RvE2 (p<.01 for condition), while there was no effect for RvE1 (p>.05 for condition or condition*day interaction). Sex-differential effects were found for two of the D-series resolvins, i.e., RvD2 and RvD4. Conclusion: This first investigation on the effects of experimental sleep disturbance on inflammatory resolution processes shows that SPMs, particularly resolvins of the D-series, are profoundly downregulated by sleep disturbances and remain downregulated after recovery sleep has been obtained, suggesting a longer lasting impact of sleep disturbances on these mediators. These findings also suggest that sleep disturbances contribute to the development and progression of a wide range of diseases characterized by immunopathology by interfering with processes that actively resolve inflammation. Pharmacological interventions aimed at promoting inflammatory resolution physiology may help to prevent future disease risk as a common consequence of sleep disturbances. Trial registration: NCT02484742.
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Study objectives: Inflammation may represent a common physiological pathway linking both short and long sleep duration to mortality. We evaluated inflammatory markers as mediators of the relationship between sleep duration and mortality in community-dwelling older adults. Design: Prospective cohort with longitudinal follow-up for mortality outcomes. Setting: Pittsburgh, Pennsylvania, and Memphis, Tennessee. Participants: Participants in the Health, Aging and Body Composition (Health ABC) Study (mean age 73.6 ± 2.9 years at baseline) were sampled and recruited from Medicare listings. Measurements and results: Baseline measures of subjective sleep duration, markers of inflammation (serum interleukin-6, tumor necrosis factor-α, and C-reactive protein) and health status were evaluated as predictors of all-cause mortality (average follow-up = 8.2 ± 2.3 years). Sleep duration was related to mortality, and age-, sex-, and race-adjusted hazard ratios (HR) were highest for those with the shortest (< 6 h HR: 1.30, CI: 1.05-1.61) and longest (> 8 h HR: 1.49, CI: 1.15-1.93) sleep durations. Adjustment for inflammatory markers and health status attenuated the HR for short (< 6 h) sleepers (HR = 1.06, 95% CI = 0.83-1.34). Age-, sex-, and race-adjusted HRs for the > 8-h sleeper group were less strongly attenuated by adjustment for inflammatory markers than by other health factors associated with poor sleep with adjusted HR = 1.23, 95% CI = 0.93-1.63. Inflammatory markers remained significantly associated with mortality. Conclusion: Inflammatory markers, lifestyle, and health status explained mortality risk associated with short sleep, while the mortality risk associated with long sleep was explained predominantly by lifestyle and health status.
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Study objectives: To investigate the comparative efficacy of cognitive behavioral therapy (CBT), Tai Chi Chih (TCC), and sleep seminar education control (SS) on the primary outcome of insomnia diagnosis, and secondary outcomes of sleep quality, fatigue, depressive symptoms, and inflammation in older adults with insomnia. Design: Randomized controlled, comparative efficacy trial. Setting: Los Angeles community. Patients: 123 older adults with chronic and primary insomnia. Interventions: Random assignment to CBT, TCC, or SS for 2-hour group sessions weekly over 4 months with follow-up at 7 and 16 months. Measurements: Insomnia diagnosis, patient-reported outcomes, polysomnography (PSG), and high-sensitivity C-reactive protein (CRP) levels. Results: CBT performed better than TCC and SS in remission of clinical insomnia as ascertained by a clinician (P < 0.01), and also showed greater and more sustained improvement in sleep quality, sleep parameters, fatigue, and depressive symptoms than TCC and SS (all P values < 0.01). As compared to SS, CBT was associated with a reduced risk of high CRP levels (> 3.0 mg/L) at 16 months (odds ratio [OR], 0.26 [95% CI, 0.07-0.97] P < 0.05). Remission of insomnia was associated with lower levels of CRP (P < 0.05) at 16 months. TCC was associated with improvements in sleep quality, fatigue, and depressive symptoms as compared to SS (all P's < 0.05), but not insomnia remission. PSG measures did not change. Conclusions: Treatment of late-life insomnia is better achieved and sustained by cognitive behavioral therapies. Insomnia treatment and remission reduces a marker of inflammatory risk, which has implications for cardiovascular morbidity and diabetes observed with sleep disturbance in epidemiologic surveys.
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Sleep has a critical role in promoting health. Research over the past decade has documented that sleep disturbance has a powerful influence on the risk of infectious disease, the occurrence and progression of several major medical illnesses including cardiovascular disease and cancer, and the incidence of depression. Increasingly, the field has focused on identifying the biological mechanisms underlying these effects. This review highlights the impact of sleep on adaptive and innate immunity, with consideration of the dynamics of sleep disturbance, sleep restriction, and insomnia on (a) antiviral immune responses with consequences for vaccine responses and infectious disease risk and (b) proinflammatory immune responses with implications for cardiovascular disease, cancer, and depression. This review also discusses the neuroendocrine and autonomic neural underpinnings linking sleep disturbance and immunity and the reciprocal links between sleep and inflammatory biology. Finally, interventions are discussed as effective strategies to improve sleep, and potential opportunities are identified to promote sleep health for therapeutic control of chronic infectious, inflammatory, and neuropsychiatric diseases. Expected final online publication date for the Annual Review of Psychology Volume 66 is November 30, 2014. Please see for revised estimates.
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We ask whether subjective socioeconomic status (SES) predicts who develops a common cold when exposed to a cold virus. 193 healthy men and women ages 21-55 years were assessed for subjective (perceived rank) and objective SES, cognitive, affective and social dispositions, and health practices. Subsequently, they were exposed by nasal drops to a rhinovirus or influenza virus and monitored in quarantine for objective signs of illness and self-reported symptoms. Infection, signs and symptoms of the common cold, and clinical illness (infection and significant objective signs of illness). Increased subjective SES was associated with decreased risk for developing a cold for both viruses. This association was independent of objective SES and of cognitive, affective and social disposition that might provide alternative spurious (third factor) explanations for the association. Poorer sleep among those with lesser subjective SES may partly mediate the association between subjective SES and colds. Increased Subjective SES is associated with less susceptibility to upper respiratory infection, and this association is independent of objective SES, suggesting the importance of perceived relative rank to health.
Good sleep is essential to good health. Yet for most of its history, sleep medicine has focused on the definition, identification, and treatment of sleep problems. Sleep health is a term that is infrequently used and even less frequently defined. It is time for us to change this. Indeed, pressures in the research, clinical, and regulatory environments require that we do so. The health of populations is increasingly defined by positive attributes such as wellness, performance, and adaptation, and not merely by the absence of disease. Sleep health can be defined in such terms. Empirical data demonstrate several dimensions of sleep that are related to health outcomes, and that can be measured with self-report and objective methods. One suggested definition of sleep health and a description of self-report items for measuring it are provided as examples. The concept of sleep health synergizes with other health care agendas, such as empowering individuals and communities, improving population health, and reducing health care costs. Promoting sleep health also offers the field of sleep medicine new research and clinical opportunities. In this sense, defining sleep health is vital not only to the health of populations and individuals, but also to the health of sleep medicine itself. Buysse DJ. Sleep health: can we define it? Does it matter? SLEEP 2014;37(1):9-17.