Social relationships, sleep quality, and interleukin-6
in aging women
Elliot M. Friedman*†, Mary S. Hayney‡, Gayle D. Love§, Heather L. Urry¶, Melissa A. Rosenkranz¶, Richard J. Davidson¶,
Burton H. Singer†?, and Carol D. Ryff§
*Robert Wood Johnson Health & Society Scholars Program, Department of Population Health Sciences,‡School of Pharmacy,§Institute on Aging, and
¶Department of Psychology, University of Wisconsin, Madison, WI 53726; and?Office of Population Research, Princeton University, Princeton, NJ 08544
Contributed by Burton H. Singer, October 24, 2005
This study examined the interplay of social engagement, sleep
quality, and plasma levels of interleukin-6 (IL-6) in a sample of
aging women (n ? 74, aged 61–90, M age ? 73.4). Social engage-
ment was assessed by questionnaire, sleep was assessed by using
the NightCap in-home sleep monitoring system and the Pittsburgh
Sleep Quality Index, and blood samples were obtained for analysis
of plasma levels of IL-6. Regarding subjective assessment, poorer
sleep (higher scores on the Pittsburgh Sleep Quality Index) was
associated with lower positive social relations scores. Multivariate
regression analyses showed that lower levels of plasma IL-6 were
predicted by greater sleep efficiency (P < 0.001), measured objec-
tively and by more positive social relations (P < 0.05). A significant
interaction showed that women with the highest IL-6 levels were
those with both poor sleep efficiency and poor social relations (P <
0.05). However, those with low sleep efficiency but compensating
good relationships as well as women with poor relationships but
compensating high sleep efficiency had IL-6 levels comparable to
those with the protective influences of both good social ties and
for negative health outcomes. In particular, we focus on sleep
quality and its interactions with social engagement in predicting
factors because all have been linked with important health out-
comes and with aging processes. For example, IL-6, an inflamma-
tory factor whose concentration generally increases in the blood
with age (1–6), has been linked with Alzheimer’s disease, osteo-
porosis, rheumatoid arthritis, cardiovascular disease, and some
forms of cancer (1, 2, 5–7), and it is prospectively associated with
general disability (3) and mortality (8) in large population-based
poor sleep quality increases the risk of mortality (12). Low sleep
quality has also been linked to elevated IL-6 levels in patients with
clinical sleep disorders (13) and experimental studies involving
healthy volunteers (14–16). Social relationships, in addition, have
been linked with sleep quality. Whether measured objectively or
subjectively, sleep efficiency is lower and time awake during the
18). Self-reported sleep quality is also lower in married men and
women who report higher levels of attachment anxiety, an effect
that is independent of depressive affect (13). Potential links be-
tween social relationships and IL-6 are less well established, al-
though we recently reported that positive relations with others
significantly predicted lower plasma levels of IL-6 in aging
together to assess whether the optimally low IL-6 profile would be
and good sleep quality and, conversely, whether those with high
levels of IL-6 would lack both protective influences. Such inquiry
n this study, we probe an elderly population to identify social and
behavioral factors that may characterize persons at reduced risk
we were also interested in possible compensatory (interactive)
influences, for example, whether those with poor sleep quality who
nonetheless had good quality relationships and those with poor
quality relationships who had good quality sleep might also show
lower levels of IL-6. A further possibility is that sleep quality
mediates the association of social relations and plasma IL-6. Our
analyses tested for both moderating and mediating influences (20).
Such inquiry responds to the growing interest in factors that
call for integrative studies that combine influences on health across
multiple domains (psychological, social, behavioral, and biological)
(16). We tested these relationships by using self-reported and
objective sleep assessments. The NightCap system provides objec-
tive measures of sleep latency, total sleep duration, duration of
rapid eye movement (REM) and non-rapid eye movement
(NREM) stages, and sleep efficiency. Use of the NightCap system
facilitated data collection in participants’ homes, and the data
obtained previously has compared favorably to those gathered in
the laboratory (21, 22). This method was used to examine the
impact of loneliness on sleep (17). Participants also completed the
Pittsburgh Sleep Quality Index (PSQI), a measure of self-rated
sleep quality (19). Positive social engagement was operationalized
by using the positive relations with others scale, one of Ryff’s six
linked to several biological markers of health (24, 25), including
plasma IL-6 (unpublished data).
Participants. Respondents from a prior longitudinal study of aging
(see refs. 26 and 27) were contacted by mail and invited to
participate in an additional study involving biomarker data collec-
tion, and volunteers were enrolled until a target number of 135 was
reached. There were no inclusion or exclusion criteria, except the
ability and willingness to travel to the General Clinical Research
Center (GCRC) on the University of Wisconsin, Madison campus
for an overnight stay. Consent for all procedures was obtained
during the GCRC visit. Among those who did not participate, 16%
were ineligible (because of death, severe morbidity, or moving out
of difficulties with travel or for reasons of health). However, this
newly recruited biomarker sample of 135 participants was not
significantly different from the original longitudinal sample with
regard to health (chronic conditions and health symptoms), in-
come, and marital status, but was significantly younger and had
more education. The biomarker sample ranged in age from 61 to
Conflict of interest statement: No conflicts declared.
Freely available online through the PNAS open access option.
Abbreviations: GCRC, General Clinical Research Center; HPA, hypothalamic–pituitary–
†To whom correspondence may be addressed. E-mail: email@example.com or singer@
© 2005 by The National Academy of Sciences of the USA
December 20, 2005 ?
vol. 102 ?
no. 51 ?
90 with an average age of 73.4 years. Respondents had moderate
incomes and slightly more than a high school education, and more
than half (55.1%) were widowed.
respondents 3–4 weeks before their visit to the University of
Wisconsin campus for the biomarker assessments. These question-
naires were completed independently and returned to investigators
at the time of their campus visit.
Social engagement. Eudaimonic well-being refers to active engage-
ment with the existential challenges of living (see ref. 28). Social
positive relations with others eudaimonic well-being scale (23),
which was measured with 14 self-descriptive items (scale range ?
14–84). Individuals scoring high on this scale report had satisfying
and trusting relationships with others and concern for the welfare
of others. For example, a high score on the item ‘‘I feel that I get
a lot out of my friendships’’ would indicate higher levels of positive
relations, whereas a high score on the item ‘‘I often feel as if I’m on
the outside looking in when it comes to friendships’’ would indicate
with the five other scales of psychological well-being (23) in studies
of marital transitions (20), community relocation (26), and biolog-
ical markers of disease (29). The ? coefficient for this scale, a
measure of the internal consistency of the scale items, was 0.88.
Previous publications have documented the validity of this scale
packet that participants completed before their GCRC stay. Par-
ticipants are asked about their sleep habits during the preceding
month. The PSQI has 17 items, most of which are rated on a
four-point Likert scale, designed to assess seven components of
sleep: subjective sleep quality, sleep latency, sleep duration, habit-
ual sleep efficiency, sleep disturbances, use of sleeping medication,
and daytime dysfunction. These items generate a global score with
significant sleep problems (19). The PSQI has well established
reliability and validity and is widely used in clinical research.
Health behaviors. Tobacco and alcohol use are known to influence
both sleep and plasma IL-6 levels (31–34). To control for potential
confounding effects, smoking and alcohol consumption by study
participants was determined from the self-administered question-
naires. None of the participants was a current smoker, whereas 36
smoking history was included in statistical analyses. Thirty-one
participants (39.7%) responded that there was a time in their lives
when they consumed at least one drink 3 days a week. This
dummy-coded variable was also included in statistical analyses.
GCRC Health Assessments. Participants were admitted to the GCRC
located within the University of Wisconsin Hospital and Clinics for
an overnight stay. A trained nurse or physician took the respon-
a summary variable was created from specific items related to
overall health, inflammatory conditions, immune-related diseases,
medical history of allergies, asthma, diabetes, cancer or leukemia,
hypertension, heart trouble or disease, or arthritis or rheumatism.
were also selected to control for potential effects on IL-6. Because
IL-6 has been linked to obesity (35, 36), waist?hip ratio was
basis of waist circumference (measured at its narrowest point
between the ribs and iliac crest), and hip circumference (measured
at the maximal point of the buttocks).
During GCRC visits, use of prescription and over-the-counter
medications was recorded and coded. To control for the possible
effects of medications on IL-6 levels, a variable was created to
indicate the use of antiinflammatory and psychoactive medications
and antihistamines, including salicylates and steroidal and nonste-
roidal anti-inflammatory drugs (coded as use and nonuse of any of
first step along with other control variables. Because antioxidant
vitamins (e.g., vitamins A, C, and E) were being used by ?90% of
participants, no variable was created to control for their impact on
Cytokine Measures. In-home resting blood samples were obtained
from participants by trained nurses with standard phlebotomy
techniques. Samples were centrifuged and the plasma fraction
aliquoted and stored at ?80°C until analyzed. IL-6 concentrations
were measured in duplicate by using ELISA (Quantikine HS High
Sensitivity human IL-6; R & D Systems, Minneapolis) according to
because of the vaccination schedule, the period between each
participant’s visit to the GCRC and the blood samples varied,
although ?50% of samples were collected within 9 months of the
GCRC visit. To control for any systematic effects of these differ-
ences, the time elapsed between the GCRC visit and the blood
draws for each individual was entered into regression models as a
control variable. Immunizations were scheduled to coincide with
flu season, and so all blood samples were obtained between
October and December, and all sampling occurred after partici-
pants had visited the GCRC. Blood draws were scheduled at the
convenience of the participants, and so time of day was not
consistent (although all samples were obtained during daylight
NightCap Sleep Recordings. Participants received instructions on
using the NightCap and wore the NightCap for 1 night during their
stay at the GCRC. They then collected sleep data for 4 consecutive
nights at home immediately after their stay at the GCRC. Explor-
atory analyses showed that sleep parameters during the 4 nights at
home were similar to one another and of better quality than the
night in the GCRC.
The NightCap is a two-channel device that records eye and head
movements by using sensors that are mounted in a bandana worn
on the head during each night of sleep. The eye sensor consists of
eyelid. Head motions are detected with a multipolar cylindrical
mercury switch on the forehead. Activity in these sensors is
The algorithm used by the NightCap system, which is described in
Ajilore et al. (22), essentially distinguishes three sleep?wake states
across samples for each minute of sleep: wake (activity in both eye
REM (eyelid activity only).
Artifact prone data were discarded, as were the data from the
first night of sleep at the GCRC, which was considered to be an
accommodation night. Estimates of time in bed, sleep duration,
sleep efficiency (sleep duration as a function of total time in bed),
NREM time, and mean REM time were determined for each
participant for each night of sleep. Subjects having at least two
nights of good data after the accommodation night were retained
length, different sleep states (awake, NREM, and REM) were
expressed as a percent of total time in bed.
Statistical Analysis. Associations among sleep parameters, sociode-
positive relations with others were examined initially with bivariate
analyses. Multivariate linear regression analyses were then used to
www.pnas.org?cgi?doi?10.1073?pnas.0509281102 Friedman et al.
variables included age, marital status, years of education, pretax
family income, chronic health conditions, medication use, and
health behavior. An ? level of 0.05 was used to determine statis-
tically significant associations.
Participant characteristics are shown in Table 1. On average, the
women in this study had ?2 years of college education, a median
income of $25,000, and relatively high scores on the positive
almost 68% scoring above 5 on the PSQI, an indication of signif-
icant problems in at least two components of sleep (19).
Table 2 summarizes the bivariate relationships between self-
reported and objective sleep parameters, positive relations with
others, plasma IL-6, and age. Higher PSQI global scores were
significantly correlated with greater sleep latency and marginally
correlated with deceased time in NREM sleep. Higher scores on
the positive relations with others scale were significantly correlated
with lower PSQI global scores and marginally correlated with
reduced sleep latency. Greater sleep efficiency, lower PSQI global
lower plasma IL-6 at the bivariate level. Finally, increased age
significantly predicted reduced sleep efficiency, more body move-
the bivariate relationships between plasma IL-6 and scores on the
positive relations with others scale (Fig. 1A) and sleep efficiency
Multivariate linear regression analyses were conducted to deter-
mine whether positive relations with others and sleep measures
independently predicted IL-6 net of sociodemographic, health, and
health behavior control variables, and the results of these analyses
significantly predicted plasma IL-6 levels (Fig. 2). These relation-
ships were in the expected directions, with greater sleep efficiency
Table 1. Descriptive statistics for study participants (n ? 78)
Years of education
Median pretax family income, $
No. of medications
No. of chronic health conditions
Total time in bed, min
Total sleep duration, min
Latency to sleep onset, min
Latency to REM onset, min
Percent time awake (of time in bed)
Percent time in NREM sleep
Percent time in REM sleep
Percent time body moving
Sleep efficiency (time asleep?time in bed)
PSQI global score (scale range 0–21)
Score ? 5
Positive relations with others (scale range 14–84)
Plasma IL-6, pg?ml
Table 2. Bivariate relationships among polysomnographic and self-rated sleep measures,
positive relations with others, plasma IL-6, and age
Total sleep duration, trimmed
Sleep efficiency, cubed
Latency to sleep onset, trimmed
Latency to REM onset, trimmed
Percent NREM sleep
Percent REM sleep
Percent body moving
PSQI global score
Positive relations, cubed
Plasma IL-6 (log)
Data transformations are noted.*, P ? 0.001; †, P ? 0.05; ‡, P ? 0.10; §, P ? 0.01.
Friedman et al.
December 20, 2005 ?
vol. 102 ?
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IL-6 levels. Although latency to sleep onset predicted IL-6 levels at
the bivariate level, the association was not significant once the
control variables were included in the regression analysis (data not
shown). PSQI global scores were also not significantly related to
plasma IL-6 levels (data not shown).
positive relations with others were entered into a regression model,
interaction between these two measures (Table 3, Model 3; P ?
0.05). As shown in Fig. 2, IL-6 levels were highest in women with
poor sleep quality who also scored low on the positive relations
scale; women with good sleep quality or strong social relationships
or both all had lower IL-6 levels. In this last regression model,
positive relations with others, sleep efficiency, and the interaction
term accounted for 34% of the variance in plasma IL-6 (change in
R2? 0.34, P ? 0.001).
Finally, to test the possibility that sleep quality mediates the
association between positive relations with others and plasma IL-6,
relations (Table 3, Model 4). This analysis showed that when both
terms were in the regression model, sleep efficiency and positive
relations independently predicted IL-6 levels, suggesting that sleep
efficiency did not mediate the association of positive relations and
This study tested the hypotheses that both social engagement and
sleep quality would predict plasma IL-6 levels in aging women and
among these predictor variables. The results provided support for
and positive relations with others significantly predicted levels of
IL-6 in the hypothesized direction. These findings are consistent
with previous research (38–42) but extend prior findings in impor-
tant directions with regard to the size of the aging sample and the
comprehensiveness of both the sleep assessments and the control
variables (age, marital status, health problems, medication use,
smoking, alcohol consumption, and subjective sleep quality). Re-
garding the interplay of social ties and sleep on IL-6 levels, we also
found evidence of compensatory effects. That is, although women
of IL-6, it was also the case that those who had good relationships
but poor sleep efficiency, or had good sleep efficiency but poor
social relations, had comparably low levels of IL-6. Such findings
underscore the protective influence of psychosocial and behavioral
factors; the strengths of one compensate for the deficiencies of the
other. Clearly the most disadvantaged respondents were those with
both poor sleep efficiency and low quality social connections with
others, but focusing on only this outcome misses the important and
frequently overlooked evidence regarding the factors that may
protect against age-related increases in inflammation, even in the
face of other psychosocial or behavioral risks. As such, the findings
join a growing literature that is mapping diverse pathways toward
the maintenance of health in aging individuals (43, 44).
The results also foreshadow further mechanistic relationships
that may underlie the linkages among sleep quality, social engage-
ment, and inflammation in aging women. One implication of the
interaction between sleep efficiency and positive relations with
others is that both may be linked to IL-6 by way of a common
tertiary mechanism, possibly the hypothalamic–pituitary–adrenal
(HPA) axis. Sleep disruption in the laboratory, for example, is
associated with alterations in HPA activity (45), and age-related
changes in sleep are linked to dysregulation of the HPA axis (46,
47). Psychological stress and clinical depression, both of which are
associated with HPA dysfunction (48, 49), are also linked to
impaired regulation of IL-6 production, at least in immunocom-
petant cells (50). The ability of glucocorticoids to restrain IL-6
production in vitro, for example, is impaired in individuals experi-
encing chronic stress (51). Significantly, however, social support
partially restores sensitivity to regulation by glucocorticoids regu-
lation (51). It is conceivable that sleep quality and social engage-
ment converge in preserving HPA regulation in aging women and,
thereby, regulation of IL-6 production. The potential for mecha-
nistic links between social engagement and specific aspects of brain
and neuroendocrine function is underscored by recent research
efficiency with IL-6. (A) Bivariate scatter plot of the association of positive
relations with others and plasma IL-6. There was a significant negative asso-
ciation between these variables, with higher scores on the positive relations
measure predicting lower levels of IL-6 (R ? ?0.34, P ? 0.01). Data transfor-
association of sleep efficiency and plasma IL-6. There was a significant nega-
tive association between these variables, with higher scores on the positive
relations measure predicting lower levels of IL-6 (R ? ?0.44, P ? 0.001). Data
transformations are indicated on the figure axis labels.
Bivariate associations of positive relations with others and sleep
www.pnas.org?cgi?doi?10.1073?pnas.0509281102Friedman et al.
showing that greater left frontal brain activation, measured by
electroencephalography, is significantly associated with higher
scores on the positive relations scale (52). This speculation suggests
a number of testable hypotheses involving simultaneous assess-
ments of sleep quality, social engagement, HPA function, and IL-6.
The relationship between sleep quality and IL-6 may be recip-
rocal; indeed, evidence is accumulating in both animal and human
studies to suggest that IL-6 may modulate sleep. For example, IL-6
levels exhibit a circadian pattern that corresponds to the human
sleep cycle, with peak values at night and nadirs during the day (53,
54). Endogenous IL-6 may contribute to excessive daytime sleep-
is elevated. Evidence in mice probes underlying mechanisms,
suggesting that IL-6 does not impact NREMs, possibly due to low
levels of the protein in the brain, whereas knockout mice lacking
genes for IL-6 were found to spend more time in REMs after sleep
deprivation (55). These lines of research suggest that IL-6 may be
involved in physiological sleep regulation.
Aging processes set the context for this inquiry. As such, it is
important to note that age alone significantly predicted both sleep
quality and plasma IL-6 levels in this sample. At the bivariate level,
advancing age was associated with decreased sleep efficiency,
although not with subjective sleep quality. However, regression
mediated by the presence of chronic health conditions and health-
driven limitations on activity (data not shown). These findings are
consistent with the suggestion that age-related sleep impairments
are not due to aging per se but rather to the presence of age-related
diseases (10, 56, 57). In contrast, the association of age with plasma
IL-6 levels was independent of the health indicators included in the
regression models, an observation that is consistent with previous
reports of age-related increases in IL-6 (1, 3, 4, 6). We probed for
ill health in a number of ways (chronic conditions, number of sick
days, visits to doctor in past year, and health problems in daily
activities). These variables were all included in regression models
not shown). Although it is still possible that undetected and
unperceived disease processes, rather than aging, contributed to
higher IL-6 levels in these older women, it seems likely that other
factors also associated with aging, such as changes in psychological
example, that the rate of IL-6 accumulation in the blood with age
issue will require longitudinal collection of health and cytokine
Although the combined assessments of objective and subjective
sleep quality, social engagement, and inflammation represent
strengths of this study, interpretations of the findings should be
tempered given the homogeneity of the sample, its relatively small
size, and the cross-sectional design. Better understanding of these
diverse samples and time-coordinated assessments of key variables.
Collection of behavioral, psychological, and biological data at
multiple times, for example, will enable us to determine whether
reciprocally, whether IL-6 predicts later sleep problems and?or
to this topic would be investigations of the impact of disruption of
on changes in sleep character and quality. There is currently a lack
sleep in animals, despite the quite elaborate literature focused on
the immune systems and sleep (58).
data and the collection of blood samples for cytokine analyses was
significant in some cases. This temporal slippage was not ideal,
especially if any of the variables of interest showed limited stability
over time. We reasoned, however, that if sleep quality, social
Table 3. Multivariate linear regressions of sleep parameters and positive relations with others
on plasma IL-6 levels in aging women (n ? 78)
Predictors Model 1 (?) Model 2 (?) Model 3 (?) Model 4 (?)
Positive relations with others, cubed
Sleep efficiency, cubed
Positive relations ? sleep efficiency interaction
Change in R2
change in R2is net of the control variables. Models 1 and 2 show the individual contributions of positive relations
and sleep efficiency to plasma IL-6 levels. Model 3 shows the interaction of sleep efficiency and positive relations
in predicting IL-6. Model 4 tested the extent to which sleep efficiency and positive relations independently
predicted IL-6 levels. Models controlled for age, marital status, years of education, pretax family income, chronic
health conditions, medication use, alcohol consumption, and smoking.*, P ? 0.01; †, P ? 0.001; ‡, P ? 0.05.
interaction significantly predicted plasma IL-6 levels (? ? 1.19, P ? 0.05). The
data points shown were calculated from the same regression equation. So-
to their mean values. Maximal or minimal values for sleep efficiency and
positive relations predictor variables were then added to the equation to
generate the estimates shown here (37).
Interaction of sleep efficiency and positive relations with others. The
Friedman et al.
December 20, 2005 ?
vol. 102 ?
no. 51 ?
relations scores, or plasma IL-6 levels were highly fluctuating,
time-dependent domains, it would reduce the likelihood of observ-
ing significant relationships among them. As such, the data we had
available translated to a relatively conservative test of our hypoth-
eses, and the results suggest, in part because of the temporal
Increased variability in psychological and biological functioning
with age is a key issue undergirding this study. Most research,
however, has focused on changes in average levels of function.
Increases in IL-6 that typically occur with age, for example, are
linked to increased risk of disease, disability, and mortality (1–3,
6–8, 59–62). As a consequence, less attention has been paid to the
variance in markers of aging (15). The results of this study indicate
that although poor social relationships and poor sleep quality
scores on either variable also compensate for the presence of low
those in women with both strong social relationships and high
quality sleep. Thus, these findings suggest that strong social rela-
tionships and good quality sleep contribute, additively and inter-
actively, to advantaged biological profiles in aging women. They
also offer a potential target for interventions designed to increase
given the steadily rising proportion of older adults in western
countries, particularly the United States.
This research was supported by the Robert Wood Johnson Foundation,
National Institute on Aging Grant P01-AG020166, National Institute of
Mental Health Grant P50-MH61083, and National Institutes of Health
Grant M01-RR03186 (to GCRC, University of Wisconsin).
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