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Sleep Duration and Health-Related Quality of Life among Older Adults: A Population-Based Cohort in Spain

Authors:
  • Unidad de Investigación Conjunta en Ingeniería Biomédica

Abstract

The few studies that have addressed the association between sleep duration and health-related quality of life (HRQL) were cross-sectional and small-sized, targeted young and middle-aged persons, and did not adjust for the main confounders. This study sought to examine the cross-sectional and longitudinal relationship between habitual sleep duration and HRQL in older adults. Prospective study conducted from 2001 through 2003. Sleep duration was self-reported in 2001, and HRQL was measured using the SF-36 questionnaire in 2001 and 2003. Analyses were adjusted for the main confounders. Community-based study. A cohort of 3834 persons representative of the non-institutionalized Spanish population aged 60 years and over. None. In comparison with women who slept 7 hours, those with extreme sleep durations (< or = 5 or > or = 10 h) reported worse scores on the SF-36 physical and mental scales in 2001. Among men, sleeping < or = 5 h was associated with a worse score in the role-physical scale in 2001. The magnitude of most of these associations was comparable with the reduction in HRQL associated with aging 10 years. Sleep duration in 2001 failed to predict changes in HRQL between 2001 and 2003. Extreme sleep durations are a marker of worse HRQL in the elderly.
SLEEP, Vol. 32, No. 8, 2009 1059
SEVERAL EPIDEMIOLOGIC STUDIES HAVE OBSERVED
THAT SLEEP DURATION IS ASSOCIATED WITH HIGHER
MORBIDITY. HENCE, IN COMPARISON WITH PERSONS
who sleep 7-8 hours, those sleeping either more or fewer hours
have a higher risk of coronary disease,1,2 arterial hypertension,3
diabetes,4,5 and obesity.6-8 The impact of sleep on health is wide
ranging and manifests as higher general mortality among per-
sons with very short- or long-duration sleep.2,6,9-11
In addition to general mortality, a useful variable for assess-
ing the global impact of sleep on health is health-related quality
of life (HRQL) because it represents the individual perception
of how a health problem can affect various spheres of life,
physical as well as mental or social. Moreover, sleep duration
may possibly affect HRQL even before it has made a sizeable
impact on morbidity. To our knowledge, only two papers have
previously examined this issue.12,13 The rst analyzed the results
of 2 small-sized, cross-sectional studies on university students,
and reported no relationship between sleep duration and HRQL
as measured by the Cornell Medical Index12; the second paper,
based on cross-sectional analysis of data on 273 persons aged
40–64 years likewise reported no association between sleep
duration and HRQL measured with the Quality of Well-Being
Scale.13 However, these studies did not differentiate between
short- and long-duration sleep, and did not adjust their analy-
ses for potential confounders, whether lifestyles or chronic dis-
eases. Furthermore, since both sleep duration14,15 and HRQL16,17
decline with age, the results of these 2 studies might not apply
to the elderly.
Accordingly, this study assessed the cross-sectional relation-
ship between habitual sleep duration and HRQL among the
older adult population of Spain. In addition, it examined the
longitudinal association between sleep duration and change in
HRQL over 2 years of follow-up.
METHODS
Study Design and Participants
The study methods have been reported elsewhere.8,18 This
was a prospective, population-based cohort study. The cohort
was established in 2001 and followed up over 2 years. In 2001,
information was obtained on 4008 persons (1739 men and 2269
women) representative of the non-institutionalized Spanish
population aged 60 years and over. Subjects were selected us- Subjects were selected us-
ing probabilistic sampling by multistage clusters. The clusters
were stratied by region of residence and size of municipal-
ity. Census sections were then chosen randomly within each
cluster, and the households in which information was nally
obtained from the subjects were chosen within each section.
Information was collected from a total of 420 census sections
in Spain, and subjects were selected in age and sex strata. Sub-
jects were replaced for interviews only after 10 failed visits by
the interviewer, disability, death, institutionalization, or refusal
SLEEP DURATION AND QUALITY OF LIFE IN OLDER ADULTS
Sleep Duration and Health-Related Quality of Life among Older Adults:
A Population-Based Cohort in Spain
Raquel Faubel, PhD; Esther Lopez-Garcia, PhD; Pilar Guallar-Castillón, MD, PhD; Teresa Balboa-Castillo, BSc (Kin); Juan Luis Gutiérrez-Fisac, MD, PhD;
José R. Banegas, MD, PhD; Fernando Rodríguez-Artalejo, MD, PhD
Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid – CIBER in Epidemiology and
Public Health ( CIBERESP), Madrid, Spain
Study Objectives: The few studies that have addressed the associa-
tion between sleep duration and health-related quality of life (HRQL)
were cross-sectional and small-sized, targeted young and middle-aged
persons, and did not adjust for the main confounders. This study sought
to examine the cross-sectional and longitudinal relationship between
habitual sleep duration and HRQL in older adults.
Design: Prospective study conducted from 2001 through 2003. Sleep
duration was self-reported in 2001, and HRQL was measured using the
SF-36 questionnaire in 2001 and 2003. Analyses were adjusted for the
main confounders.
Setting: Community-based study.
Participants: A cohort of 3834 persons representative of the non-insti-
tutionalized Spanish population aged 60 years and over.
Intervention: None.
Measurement and Results: In comparison with women who slept 7
hours, those with extreme sleep durations (≤ 5 or ≥ 10 h) reported
worse scores on the SF-36 physical and mental scales in 2001. Among
men, sleeping ≤ 5 h was associated with a worse score in the role-
physical scale in 2001. The magnitude of most of these associations
was comparable with the reduction in HRQL associated with aging 10
years. Sleep duration in 2001 failed to predict changes in HRQL be-
tween 2001 and 2003.
Conclusion: Extreme sleep durations are a marker of worse HRQL in
the elderly.
Keywords: Health-related quality of life, sleep, elderly, Spain
Citation: Faubel R; Lopez-Garcia E; Guallar-Castillón P; Balboa-Cas-
tillo T; Gutiérrez-Fisac JL; Banegas JR; Rodríguez-Artalejo F. Sleep
duration and health-related quality of life among older adults: a popula-
tion-based cohort in spain. SLEEP 2009;32(8):1059-1068.
Submitted for publication May, 2008
Submitted in nal revised form May, 2009
Accepted for publication May, 2009
Address correspondence to: Dr. Fernando Rodríguez-Artalejo, Departa-
mento de Medicina Preventiva y Salud Pública., Facultad de Medicina.
Universidad Autónoma de Madrid, C/ Arzobispo Morcillo, 2, 28029 Madrid,
Spain; Tel.: +34 91 497 5444; Fax: +34 91 497 5353; E-mail: fernando.
artalejo@uam.es
Sleep Duration and Health-Related Quality of Life—Faubel et al
SLEEP, Vol. 32, No. 8, 2009 1060
to participate. The study response rate was 71%. Information
was gathered by home-based personal interview and physical
examination, undertaken by trained and certied personnel.
In 2003, an attempt was made to contact the subjects again;
of the total cohort comprising 4008 individuals, only 3235
(1411 men and 1824 women) could be tracked for follow-up.
The individuals tracked did not differ signicantly from those
lost to follow-up in any sociodemographic or lifestyle-related
characteristic, except for the number of chronic diseases diag-
nosed and reported in 2001, which was 1.4 among subjects fol-
lowed up and 1.2 among those lost to follow-up.18 In 2003, data
were collected by telephone interview conducted by trained
staff. In Spain, there is evidence that telephone information on
lifestyles and use of healthcare services is reliable and valid
against household face-to-face interviews.19,20
Informed consent to participate in the study was obtained
from each subject and an accompanying family member. The
study was approved by the Clinical Research Ethics Committee
of the “La Paz” University Hospital in Madrid, Spain.
Study Variables
Main Variables
The dependent variables were HRQL in 2001 and 2003,
measured using the Spanish version of the SF-36 question-
naire. This questionnaire is made up of 36 items, which assess
the following 8 HRQL components or scales: physical func-
tioning, role-physical, bodily pain, general health, vitality, so-
cial functioning, role-emotional, and mental health. Physical
functioning, role-physical and bodily pain reect the physical
component of health; social functioning, role-emotional and
mental health cover the psychosocial aspects; and vitality and
general health give an overall idea of subjective health, and
are thus associated with both the physical and mental aspects
of HRQL. The SF-36 allows for imputing missing data to indi-
viduals who answer more than half the items on a scale. Data
were imputed to only 321 persons in 2001 and 177 in 2003.
Subjects’ answers to any given item receive a numerical score
which, after being coded, is ranked on a scale of 0 to 100,
so that the higher the score the better the state of health.21 In
general, differences of 3 to 5 points on each scale are deemed
clinically relevant.22 The SF-36 also allows for constructing
scores that summarize the physical and mental components of
quality of life across the 8 scales. Higher scores of both the
physical summary component (PSC) and the mental summary
component (MSC) indicate better health. The Spanish version
of the SF-36 has been previously used to measure HRQL in
the elderly,16,23 and has demonstrated good reproducibility and
validity.24
The principal independent variable was habitual sleep du-
ration in 2001, ascertained with the following question: How
many hours do you usually sleep per day (including sleep at
night and during the day)? This was a closed question in which
interviewees had to report the number of hours and minutes,
which were then rounded to the nearest integer hour by the in-
terviewer. Information available did not allow distinction be-
tween sleep duration in the night and during day time (napping
or siesta).
Potential Confounders
In 2001, information was obtained on variables that, both in
the existing literature and in our study sample, have shown an
association with sleep duration, HRQL or both. Specically, sub-
jects were asked about their age, sex and leisure-time physical
activity (sedentary, occasional activity, regular activity). Weight
and height were measured using standardized procedures25; body
mass index (BMI) was calculated as weight in kilograms divided
by the square of the height in meters, with normal weight being
dened as BMI 18.5–24.9 kg/m2, overweight as BMI 25–29.9
kg/m2, and obesity as BMI ≥ 30 kg/m2.
Information was also gathered on tobacco use (never smoker,
ex-smoker, smoker) and alcohol consumption (never drinker,
ex-drinker, moderate consumption, and excess consumption).
The threshold between excess and moderate consumption was
alcohol intake > 20 g/day in women and > 30 g/day in men.
Data were likewise collected on coffee consumption (no con-
sumption, < 1, 1-2, > 2 cups/day), educational level (no formal
education, primary, secondary, and university education) and
social network, assessed as the number of participants’ social
ties (marital status, cohabitation, frequent contact with friends,
and frequent contact with family).26
Cognitive function was measured with the Mini-Examen
Cognoscitivo (MEC), a version of the Mini-Mental State Ex-
amination (MMSE)27 that has been adapted and validated for
use in the elderly in Spain.28 The MEC is scored from 0 to 30
points, with a higher score indicating better cognitive perform-
ance. Given the inuence of age and educational level on cog-
nitive function and the high percentage of elderly Spaniards
with low educational level, the recommended denition for
cognitive impairment in Spain is a MEC score < 23 (sensitivity
89.8% and specicity 80.8%).28
Further data were collected on the following chronic diseases
diagnosed by a physician or self-reported: chronic obstructive
pulmonary disease, ischemic heart disease, stroke, osteoarthri-
tis, cataracts without treatment, diabetes mellitus, Parkinson
disease, cancer at any site, and arterial hypertension. We also
gathered data on depression, dened as a self-reported diagno-
sis of depression or the use antidepressant medication. Previous
studies have reported good agreement between self-reported
diseases and clinical history in older adults.29,30 Lastly, partici-
pants were asked with a binary question (yes/no) whether they
awoke during the night, and whether they took anxiolytics.
In 2003, information was obtained by telephone on the above
variables with the exception of cognitive function.
Statistical Analysis
Cross-Sectional Analysis
This analysis examined the relationship between sleep duration
and HRQL in 2001. Of the 4008 study participants, we excluded
89 with extreme sleep duration values (< 4 or > 15 hours), 50 with
missing data on more than half the items in any SF-36 scale, and
35 who lacked data on confounders. Thus, the analyses were con-
ducted with 3834 individuals (1684 men and 2150 women).
The study associations were summarized with β coefcients
and their 95% condence intervals (CI) obtained from multiple
Sleep Duration and Health-Related Quality of Life—Faubel et al
SLEEP, Vol. 32, No. 8, 2009 1061
linear regression; the dependent variable was HRQL in 2001,
and the principal independent variable was sleep duration in
2001. Sleep duration in hours was modeled with dummies be-
cause in previous studies the relationship between sleep and
other health variables was not monotonic.6,7,11 The category of
7 h of sleep was used as reference to allow for comparison with
earlier studies on older adults.8,31-33 Two regression models were
constructed. Model 1 was adjusted for age only. Since many
of the lifestyles and chronic diseases listed above as potential
confounders may be a consequence of or be aggravated by ex-
treme sleep durations, they could be intermediary elements in
the relationship between sleep duration and HRQL; and in such
a case, it would not be appropriate to adjust for them. Model 2
was adjusted for age as well as all potential confounders mea-
sured in 2001. This model is appropriate when these variables
inuence sleep duration and are associated with HRQL, that
is, they act as genuine confounders. All potential confounders
were modeled with dummies.
Longitudinal Analysis
To examine whether sleep duration in 2001 predicted the
change in HRQL between 2001 and 2003, we used information
on the 3235 participants who could be followed up. Of these,
we excluded 245 due to death, 602 for not answering the ques-
tionnaire personally, 47 due to extreme sleep duration values
(< 4 or > 15 h), 8 for lacking data on some SF-36 scale in 2001
or 2003, and 22 for not reporting on some confounder. Thus,
the analyses were conducted with 2311 individuals (992 men
and 1319 women). In comparison with the 1486 subjects who
did not provide follow-up data, the 2311 participating in the
longitudinal analysis showed similar characteristics, but were
younger (70.2 ± 6.8 years versus 74.2 ± 8.3 years), had more
social ties (2.9 ± 1.0 ties versus 2.7 ± 1.1), and had a lower fre-
quency of men (42.9% versus 45.5%), persons with no formal
education (48.1% versus 56.3%), sedentary individuals (38.3%
versus 51.4%), participants with cognitive impairment (15.1%
versus 34.0%), and subjects who awoke from sleep during the
night (13.8% versus 17.4%).
The analyses were performed using linear regression, where
the dependent variable was the difference in HRQL between
2003 and 2001, and the principal independent variable was
sleep duration in 2001. In these models, β regression coef -In these models, β regression coef-
cients assess the 2-year average change in HRQL associated
with categories of sleep duration at baseline. A positive coef-
cient means an improvement in HRQL, while a negative coef-
cient means a worsening. Two models were constructed; the
rst adjusted for HRQL in 2001 and age, and the second addi-
tionally adjusted for all potential confounders in 2001. Because
the study relationship might be inuenced by changes in po-
tential confounders over the period 2001–2003, in a secondary
analysis the models were also adjusted for the following vari-
ables in 2003: physical activity, tobacco use, alcohol consump-
tion, and social network. Adjustment was further made for the
number of diseases diagnosed in the period 2001–2003.
The analyses were performed on men and women separately,
because there are modest differences in sleep duration14 and
important differences in HRQL34 between the sexes. To test
whether the cross-sectional or longitudinal associations be-
tween sleep duration and each SF-36 scale were different in
women and men, an F test of variance was used, comparing
model 2 with 5 interaction terms (sex by sleep category) against
the same model without such terms. Statistical tests were 2-sid-
ed and statistical signicance was set at P < 0.05. The analyses
were performed with the SAS program, version 9.1 for Win-
dows.35
RESULTS
The mean age ± SD of participants was 72.3 ± 7.7 years for
women and 71.1 ± 8.1 years for men; habitual sleep duration
was 7.9 ± 1.9 h in women and 8.2 ± 2.1 h in men. Participants’
characteristics according to habitual sleep duration are de-are de-
scribed in Table 1. Compared with subjects who had extreme
sleep durations (≤ 5 h and ≥ 10 h), those who slept for 7 or
8 hours were younger, engaged in physical activity and con-
sumed alcohol more frequently, had a higher educational level,
a greater number of social ties, a lower number of chronic dis-
eases, and a lower frequency of cognitive impairment. Those
who slept fewer hours reported more frequently to be depressed
and to use anxiolytics. Lastly, the more hours a subject slept,
the more likely he/she was to awake during the night. Results
were similar in each sex.
Table 2 shows the cross-sectional association between sleep
duration and HRQL in women. Model 1, adjusted solely for
age, indicates that, compared with women who slept 7 h, those
who slept ≤ 5 h or ≥ 10 h had a lower score on all SF-36 scales,
save for bodily pain in individuals who slept ≥ 10 h. After ad-
justment for all potential confounders (model 2), statistical
signicance was lost in the role-emotional and mental health
scales in women who slept ≥ 10 h. In general, HRQL declined
progressively for sleep durations ranging from 7 to ≤ 5 or from
7 to ≥ 10 h. Model 2 shows that the association was strong, be-
cause as compared with women sleeping 7 h, those who slept ≤
5 h scored ≥ 6 points lower on most scales and 16 points lower
on the role-physical scale. The association was only slightly
weaker in those sleeping ≥ 10 h; even so, the score was ≥ 6
points lower on the physical functioning, role-physical, and
general health. In general, those with extreme sleep durations
also showed worse scores for the PSC and MSC of the SF-36,
though the magnitude of the associations was smaller than that
observed for individual scales of the SF-36; also the association
between MSC and sleeping 10 h did not achieve statistical
signicance.
Table 3 shows the cross-sectional association between sleep
duration and HRQL in men. In model 1, sleeping ≤ 5 h was
associated (P < 0.05) with worse role-physical, vitality, mental
health, and the PSC of SF-36. On the remaining scales, sleeping
≤ 5 h was also associated with a lower score, though statistical
signicance was not reached. Similarly, men who slept 10
h versus 7 h had a statistically lower score (P < 0.05) on all
SF-36 scales except for the role-emotional scale, and a higher
score on the bodily pain scale (P < 0.05). In model 2, most of
the associations lost statistical signicance; only sleeping ≤ 5 h
was associated with worse role-physical, and sleeping 9 h with
worse vitality. Step-by-step introduction of variables into mod-
el 2 showed that physical activity, number of chronic diseases,
and intake of anxiolytic medication were the variables that most
Sleep Duration and Health-Related Quality of Life—Faubel et al
SLEEP, Vol. 32, No. 8, 2009 1062
ers. Among women, the association between extreme sleep du-
ration (≤ 5 or ≥ 10 h) and most of the SF-36 scales was weaker
than that between physical activity, use of anxiolytics, number
of chronic diseases, and HRQL. It was, however, similar to the
reduction in HRQL associated with a 10-year age increase. Fur-
thermore, on some scales, such as role-physical, the reduction
in HRQL associated with sleeping ≤ 5 h (β −16.4) was compa-4) was compa-) was compa-
rable to that associated with suffering from 2 chronic diseases,
and greater than that associated with aging 20 years, not doing
any physical activity, or consuming anxiolytics. Among men,
the reduction in the role-physical score in subjects who slept for
≤ 5 h (β −11.1) was comparable to that associated with aging 20
years, not doing any physical activity, consuming anxiolytics,
or suffering from a chronic disease.
Table 5 shows the longitudinal association of sleep duration
in 2001 with change in HRQL between 2001 and 2003 among
contributed to the loss of association between sleep duration
and HRQL. Of note is that sleeping 8 or ≥ 10 h was associated
with a better bodily pain score. Yet, in the case of bodily pain,
results depend upon the reference category used for analysis,
so that when the analysis was repeated using 8 h as reference,
the association between long duration sleep and bodily pain
disappeared; in contrast, a worse score was observed among
subjects who slept ≤ 5 h (β −8.1; 95% CI −13.8 to −2.4) or 7 h
(β -6.8; 95% CI −11.2 to −2.4). When 8 h was used as reference,
none of the remaining associations was substantially modied
in men and women alike. According to the F test of variance,
the association between sleep duration and HRQL was differ-
ent (P < 0.05) for men and women on all SF-36 scales (data not
shown).
To put the study association into context, Table 4 shows the
relationship between HRQL and some of the potential confound-
Table 1—Baseline Characteristics of the Study Participants, According to Habitual Sleep Duration in 2001
Sleep duration (hours per 24-h period)
≤5hours 6hours 7hours 8hours 9hours ≥10hours P1
N=368 N=451 N=568 N=998 N=631 N=818
Sex (%)
Men 32.1 41.0 41.5 47.2 44.8 47.8 < 0.001
Women 67.9 59.0 58.5 52.8 55.2 52.2
Age (years) 2 71.4 ± 7.8 71.5 ± 7.7 70.0 ± 7.0 70.6 ± 7.3 72.1 ± 7.8 74.6 ± 8.6 < 0.001
Physical activity (%)
Inactive 49.8 41.0 38.2 43.7 50.6 55.4 < 0.001
Moderate 48.8 55.5 58.1 52.0 46.0 43.6
Regular/intense 1.4 3.5 3.7 4.3 3.4 1.0
BMI (%)
18.5-24.9 kg/m2 17.8 14.8 18.1 16.2 18.0 20.4 < 0.001
25-29.9 kg/m2 42.5 49.0 48.5 44.6 46.9 48.1
≥ 30 kg/m2 39.7 36.1 33.4 39.1 35.1 31.5
Tobacco use (%)
Non-smoker 75.6 74.0 70.9 67.5 71.1 68.8 0.02
Ex-smoker 17.1 19.1 19.9 22.8 20.9 19.8
Smoker 7.3 6.9 9.2 9.7 8.0 11.5
Alcohol (%)
Never drinker 58.6 53.1 52.5 49.4 54.9 55.9 < 0.001
Ex-drinker 11.9 10.7 8.0 9.3 10.2 12.7
Moderate consumption3 23.8 27.3 29.6 31.9 27.3 22.5
Excessive consumption4 5.6 8.8 9.9 9.4 7.7 8.8
Coffee (%)
No consumption 48.1 48.6 45.0 48.0 48.8 55.4 0.02
< 1 cup/d 9.6 9.9 12.6 10.2 11.2 10.2
1-2 cups/d 27.6 25.6 23.2 24.3 24.6 20.3
> 2 cups/d 12.6 13.5 15.3 15.0 12.4 12.2
Education (%)
No formal 53.3 49.1 48.7 48.2 55.7 61.4 < 0.001
Primary 36.6 35.4 38.4 36.0 33.5 29.2
Secondary 6.8 9.2 9.0 10.9 8.0 6.9
University 3.3 6.3 3.8 4.9 2.8 2.5
Number of social ties2 2.8 ± 1.0 2.7 ± 1.0 2.9 ± 1.0 2.9 ± 1.0 2.8 ± 1.0 2.6 ± 1.1 0.001
Number of chronic diseases 2 1.7 ± 1.2 1.4 ± 1.0 1.2 ± 1.0 1.2 ± 1.1 1.3 ± 1.1 1.4 ± 1.1 < 0.001
Depression (%) 16.9 11.5 10.7 12.3 10.6 12.2 0.06
Cognitive impairment (%) 21.8 21.2 17.2 17.1 21.9 34.2 < 0.001
Arousal from sleep at night (%) 4.0 4.9 8.6 10.7 23.7 30.7 < 0.001
Use of anxiolytics (%) 24.6 18.8 13.2 13.6 15.0 14.7 < 0.001
1Obtained from ANOVA for continuous variables and from χ2 test for categorical variables. 2Values are means (SD). 3In men ≤ 30 g alcohol/d;
in women ≤ 20 g alcohol/d. 4In men > 30 g alcohol/d; in women > 20 g alcohol/d.
Sleep Duration and Health-Related Quality of Life—Faubel et al
SLEEP, Vol. 32, No. 8, 2009 1063
example of confounding might be sleep problems, which could
lead to prolonged sleep duration in order to cover the sleeper’s
needs. There is evidence that sleep quality and satisfaction are
associated with HRQL to a greater extent than is sleep duration
per se.12,13. Although sleep quality was not measured, the analy-
ses were adjusted for quality indicators such as use of anxi-
olytics and arousal from sleep at night. Also a frequent cause
of sleep problems is sleep apnea. However, our analyses also
adjusted for BMI and frequent sleep arousal, both of which are
correlates of sleep apnea,36 so that it is unlikely that this would
affect our results. Nonetheless, there was a substantial change
in results from model 1 to model 2 in women, so that a certain
residual confounding cannot be completely ruled out. Another
cause of poor sleep is restless legs syndrome (RLS), which is
also associated with worse HRQL.37 Unfortunately, analyses
did not adjust for RLS due to lack of data.
The second explanation is reverse causation. For instance,
long-duration sleep could be an early symptom of disease; de-
spite the analyses adjusted for the number of chronic diseases
and for lifestyle habits that lead to chronic diseases, there could
be undiagnosed subclinical diseases that alter HRQL, and this
might in turn affect sleep duration. Examples of these diseases
are osteoporosis, which cause pain and can affect sleep, or ini-
tial stages of heart failure, which may reduce physical func-
tioning or vitality, and modify sleep duration. Another possible
example of reverse causation is cognitive impairment, which is
associated with extreme sleep duration (Table 1). At baseline,
the percentage of individuals with cognitive impairment was
15.1% among the 2311 participants in the longitudinal analyses
and 34% among the 1486 individuals with no follow-up data.
women. In model 1, sleeping ≤ 5 h or ≥ 10 h was associated with
a worse score on 4 of the 8 SF-36 scales. In model 2, however,
all the associations decreased in magnitude and lost statistical
signicance. Table 6 shows the longitudinal association in men.
In model 1, compared with subjects who slept 7 h, those sleep-
ing ≤ 5 h or ≥ 9 h reported worse change in role-physical scores,
and those sleeping 6 h worse change in bodily pain scores. The
results were similar in model 2, though the association between
sleeping ≥ 10 h and the change in role-physical scale lost sta-change in role-physical scale lost sta-role-physical scale lost sta-
tistical signicance. The results of the longitudinal analyses did
not vary materially in either sex when model 2 was additionally
adjusted for physical activity, tobacco use, alcohol consump-
tion, and social network in 2003, and for the number of diseases
diagnosed in the period 2001–2003 (data not shown).
Analyses were repeated including the 89 individuals who
slept < 4 h or > 15 h, and similar results were obtained (data
not shown).
DISCUSSION
Our results show that extreme sleep durations (≤ 5 or ≥ 10
h) are associated with lower HRQL in older adults, on both
physical and mental scales. However, after adjustment for po-
tential confounders, this association lost statistical signicance
in men, except for worse role-physical in those with short-du-
ration sleep. Lastly, sleep duration did not predict HRQL at 2
years of follow-up.
Basically, there are three possible explanations for the as-
sociation between sleep duration and HRQL: uncontrolled
confounding, reverse causation, and a causal relationship. An
Table 2—Beta Regression Coefcients (95% Condence Interval) of the SF-36 Scores in 2001 According to Habitual Sleep Duration in 2001
Among Women
Sleep duration (hours per 24-hour period)
  ≤5 6 7 8 9 ≥10
N  250 265 332 528 348 427
Model 1
Physical functioning −12.56 (−16.88 to −8.25)*** –4.30 (–8.53 to –0.07)* Ref. –3.37 (–6.97 to 0.23) –5.05 (–9.01 to –1.10)** –12.20 (–16.03 to –8.36)***
Role-physical −21.77 (−28.26 to −15.28)*** –4.61 (–10.98 to 1.76) Ref. –3.35 (–8.77 to 2.07) –3.85 (–9.80 to 2.10) –9.76 (–15.54 to –3.99)**
Bodily pain −13.03 (−17.71 to −8.35)*** –3.67 (–8.27 to 0.92) Ref. 0.75 (–3.16 to 4.66) 0.15 (–4.14 to 4.45) –3.32 (–7.49 to 0.85)
General health −10.35 (−13.56 to −7.14)*** –2.33 (–5.49 to 0.82) Ref. –2.50 (–5.2 to 0.2) –6.15 (–9.10 to -3.21)*** –9.93 (–12.79 to –7.07)***
Vitality −11.76 (−15.48 to −8.04)*** –3.05 (–6.70 to 0.60) Ref. –0.16 (–3.26 to 2.95) –4.75 (–8.16 to –1.34)** −7.95 (−11.26 to −4.64)***
Social functioning −10.97 (−15.43 to −6.51)** –1.57 (–5.95 to 2.81) Ref. –1.40 (–5.12 to 2.33) –4.43 (–8.52 to –0.34) −10.70 (−14.67 to −6.72)***
Role-emotional −12.58 (−18.14 to −7.02)*** 2.79 (–2.66 to 8.24) Ref. 0.41 (–4.23 to 5.06) −1.49 (−6.59 to 3.61) −5.33 (−10.28 to −0.38)*
Mental health −7.18 (−10.63 to −3.74)*** 0.35 (−3.03 to 3.73) Ref. 3.01 (0.13 to 5.89)* −0.05 (−3.21 to 3.11) −3.7 (−6.69 to −0.62)*
PSC1 −5.77 (−7.44 to −4.09) *** −2.28 (−3.93 to −0.64)** Ref. −1.57 (−2.97 to −0.17)* −2.06 (−3.60 to −0.53)** −4.20 (−5.68 to −2.71)***
MCS2 −3.52 (−5.35 to −1.68)*** 0.91 (−0.89 to 2.72) Ref. 1.19 (−0.34 to 2.72) −0.48 (−2.16 to 1.21) −1.98 (−3.62 to −0.35)*
Model 2
Physical functioning −7.15 (−11.12 to −3.18)*** −3.02 (−6.90 to 0.84) Ref. −1.59 (−4.85 to 1.68) −1.53 (−5.16 to 2.11) −6.38 (−9.96 to -2.80)***
Role-physical −16.44 (−22.86 to −10.03)*** −3.74 (−9.99 to 2.52) Ref. −1.95 (−7.23 to 3.33) −1.30 (−7.19 to 4.59) −6.11 (−11.89 to -0.33)*
Bodily pain −7.94 (−12.45 to −3.43)*** −2.64 (−7.04 to 1.75) Ref. 1.75 (−1.96 to 5.47) 2.86 (−1.28 to 6.99) 1.46 (−2.60 to 5.53)
General health −6.43 (−9.39 to −3.48)*** −1.75 (−4.62 to 1.13) Ref. −1.79 (−4.23 to 0.64) −4.20 (−6.92 to -1.49)** −6.15 (−8.81 to -3.49)***
Vitality −7.53 (−11.04 to −4.02)*** −2.62 (−6.05 to 0.79) Ref. 0.93 (−1.95 to 3.83) −2.31 (−5.53 to 0.91) −3.83 (−6.99 to -0.66)**
Social functioning −6.73 (−10.94 to −2.51)*** −1.01 (−5.11 to 3.09) Ref. 0.07 (−3.39 to 3.54) −1.05 (−4.91 to 2.81) −5.23 (−9.03 to -1.44)**
Role-emotional −8.45 (−13.87 to −3.02)** 3.02 (−2.27 to 8.31) Ref. 1.36 (−3.10 to 5.83) 0.17 (−5.15 to 4.81) −1.44 (−6.33 to 3.44)
Mental health −3.53 (−6.79 to −0.26)* 0.80 (−2.39 to 3.98) Ref. 3.71 (1.02 to 6.40)** 1.41 (−1.58 to 4.41) −0.98 (−3.92 to 1.97)
PSC1 −3.81 (−5.39 to −2.24)*** −1.84 (−3.37 to −0.30)* Ref. −1.03 (−2.33 to 0.26) −0.82 (−2.26 to 0.63) −2.25 (−3.67 to -0.83)**
MSC2 −1.99 (−3.74 to −0.23)* 0.96 (−0.75 to 2.67) Ref. 1.54 (0.09 to 2.98)* 0.17 (−1.44 to 1.79) −0.55 (−2.14 to 1.03)
*P < 0.05; **P < 0.01; ***P < 0.001. 1PSC: Physical summary component of the SF-36. 2MSC: Mental summary components of the SF-36.
Model 1: adjusted for age (60-69, 70-79, ≥ 80 years). Model 2: adjusted for age (60-69, 70-79, ≥ 80 years), physical activity (inactive, moder-
ate, regular/intense), BMI (normal weight, overweight, obesity), tobacco use (non-smoker, ex-smoker, smoker), alcohol consumption (never
drinkers, ex-drinker, moderate consumption, excess consumption), coffee consumption (no consumption, < 1, 1-2, ≥ 2 cups/day), educational
level (no formal education, primary, secondary and university education), number of social ties, number of chronic diseases (0, 1, ≥ 2), depres-
sion, cognitive impairment, arousal from sleep at night, intake of anxiolytic medication.
Sleep Duration and Health-Related Quality of Life—Faubel et al
SLEEP, Vol. 32, No. 8, 2009 1064
poor health more frequently.40 Similarly, another study on rural
elders showed that those who slept longer had worse subjec-
tive health and worse physical functioning.41 Lastly, a study on
adults aged 20 years and over observed that both short- and
long-duration sleep were associated with worse health.42 Hence,
most of the literature supports that extreme sleep durations are
associated with worse health.
Causality could also be inferred from biological plausibility.38
There is evidence of some mechanisms for the negative effects
of short-duration sleep on health. Specically, sleep restriction
produces fatigue and daytime sleepiness. Also sleep restriction
results in a series of adverse physiologic effects, such as hyper-
tension, activation of the sympathetic nervous system, impaired
glycemic control, and increased inammation markers.1,43 This
could contribute to explain the worse HRQL among short-du-
ration sleepers in the cross-sectional analyses. However, data
on mechanisms of the association between long-duration sleep
and worse HRQL are sparser still. Although further research
into the biologic and social mechanisms of the study associa-
tion is needed, it is reassuring that the strongest association,
among both sexes in the cross-sectional study and among men
in the longitudinal study, was observed between short-duration
sleep and worse role-physical, since it is clear that sleep restric-
tion causes fatigue and sleepiness. Recent data have conrmed
a worse physical performance in elderly women with extreme
sleep durations measured by actigraphy.44
An additional causality criterion is coherence with existing
epidemiologic knowledge. If sleep duration is causally asso-
ciated with HRQL, it would be expected that sleep problems,
which frequently accompany extreme sleep durations, were
Thus, longitudinal analyses were conducted on a subgroup with
better cognitive performance. If the cross-sectional association
between extreme sleep duration and worse HRQL was partly
due to reverse causation by poorer cognitive function, this
might have contributed to a lack of association in the longitudi-
nal analyses. In theory, the problem of reverse causality could
be solved through our longitudinal analysis, in which sleep du-
ration was measured before HRQL, and baseline HRQL was
additionally adjusted for. Yet, the only demonstrated effects of
sleep on health are those produced in the short term (days or
weeks).1 If these were the only important sleep effects, their
impact on HRQL could be demonstrated only with a very short
follow-up or even with a cross-sectional analysis. In our study,
there was a substantial change between the results of the cross-
sectional and the longitudinal analyses. Since the mechanisms
whereby sleep could affect health in the long term are not clear,
it is difcult to know whether the temporal relationship between
sleep and HRQL is better reected in the cross-sectional analy-
sis or in the longitudinal analysis over two years.
The third explanation for the study relationship is that sleep
duration itself causes worse HRQL. In our study, the asso-
ciations observed tend to be fairly strong, which traditionally
supports a causal relationship.38 Another classic criterion of
causality is the temporal relationship of the association, com-
mented above. A further criterion is consistency across stud-
ies. Our results can be compared with those of studies on sleep
duration and self-rated health, which roughly coincide with the
SF-36 general health scale. One study on adults aged 50–65
years reported no signicant associations.39 In an international
study, however, university students who slept < 7 h reported
Table 3—Beta Regression Coefcients (95% Condence Interval) of the SF-36 Scores in 2001 According to Habitual Sleep Duration in 2001
Among Men
Sleep duration (hours per 24-hour period)
  ≤5 6 7 8 9 ≥10
n  118 185 236 470 283 392
Model 1
Physical functioning −5.75 (−12.03 to 0.53) −2.65 (−8.13 to 2.82) Ref. −1.19 (−5.64 to 3.25) −4.47 (−9.40 to 0.45) −7.41 (−12.03 to −2.80)***
Role-physical −15.90 (−24.89 to −6.92)*** −3.63 (−11.47 to 4.21) Ref. −4.16 (−10.52 to 2.20) −5.53 (−2.58 to 1.52) −7.71 (−14.32 to −1.10)*
Bodily pain −5.27 (−11.79 to 1.25) 1.24 (−4.44 to 6.93) Ref. 6.45 (1.84 to 11.07)** 2.23 (−2.89 to 7.34) 5.32 (0.52 to 10.11)*
General health −4.56 (−9.66 to 0.55) −2.81 (−7.27 to 1.64) Ref. 0.83 (−2.78 to 4.45) −4.37 (−8.37 to −0.36)* −5.53 (−9.29 to −1.78)**
Vitality −8.09 (−13.59 to −2.58)* −3.40 (−8.20 to 1.41) Ref. −2.19 (−6.09 to 1.70) −7.78 (−12.10 to −3.46)** −8.72 (−12.77 to −4.67)***
Social functioning −3.76 (−9.54 to 2.02) −3.26 (−8.30 to 1.78) Ref. −3.56 (−7.65 to 0.53) −0.94 (−5.47 to 3.60) −6.82 (−11.07 to −2.57)**
Role-emotional −1.99 (−8.39 to 4.42) −3.06 (−8.65 to 2.52) Ref. −0.53 (−5.06 to 4.00) 0.93 (−4.09 to 5.95) −2.34 (−7.05 to 2.37)
Mental health −4.85 (−9.55 to −0.16)* −4.44 (−8.54 to −0.35)* Ref. −0.26 (−3.59 to 3.06) -0.81 (−4.49 to 2.87) −4.07 (−7.52 to −0.61)*
PSC1 −3.28 (−5.73 to −0.82)** −0.37 (−2.51 to 1.77) Ref. 0.23 (−1.50 to 1.97) −1.76 (−3.68 to 0.17) −1.72 (−3.52 to 0.086)
MCS2 −1.28 (−3.54 to 0.98) −2.02 (−3.99 to −0.04)* Ref. −0.85 (−2.45 to 0.75) −0.29 (−2.07 to 1.48) −2.27 (−3.93 to −0.60)**
Model 2
Physical functioning −1.18 (−6.71 to 4.35) −0.73 (−4.13 to 5.59) Ref. 0.20 (−3.71 to 4.11) −1.40 (−5.76 to 2.95) −0.63 (−3.54 to 4.81)
Role-physical −11.10 (−19.73 to −2.46)* −0.88 (−8.47 to 6.70) Ref. −3.62 (−9.73 to 2.48) −4.46 (−11.27 to 2.35) −1.78 (−8.30 to 4.75)
Bodily pain −1.59 (−7.73 to 4.55) 3.01 (−2.39 to 8.40) Ref. 6.56 (2.22 to 10.91)** 4.65 (−0.19 to 9.50) 9.46 (4.82 to 14.10)***
General health −0.64 (−5.16 to 3.88) 0.13 (−3.84 to 4.09) Ref. 1.56 (−1.63 to 4.76) −1.49 (−5.06 to 2.07) 0.67 (−2.74 to 4.08)
Vitality −4.45 (−9.45 to 0.55) −0.55 (−4.94 to 3.84) Ref. −1.81 (−5.34 to 1.72) −5.84 (−9.79 to −1.90)** −2.22 (−6.00 to 1.56)
Social functioning −0.37 (−5.63 to 4.89) −0.69 (−5.31 to 3.91) Ref. −2.67 (−6.38 to 1.05) 0.53 (−3.61 to 4.68) −0.26 (−4.23 to 3.72)
Role-emotional 1.74 (−4.36 to 7.84) −1.12 (−6.47 to 4.23) Ref. 0.22 (−4.09 to 4.53) 1.53 (−3.28 to 6.33) 1.35 (−3.26 to 5.95)
Mental health −0.76 (−5.02 to 3.50) −1.30 (−5.05 to 2.44) Ref. 0.54 (−2.47 to 3.55) −0.02 (−3.37 to 3.34) −0.50 (−3.71 to 2.72)
PSC1 −1.74 (−3.95 to 0.47) 0.63 (−1.31 to 2.57) Ref. 0.49 (−1.07 to 2.06) −0.55 (−2.29 to 1.19) 1.05 (−0.62 to 2.72)
MSC2 0.30 (−1.77 to 2.37) −0.85 (−2.67 to 0.97) Ref. −0.54 (−2.01 to 0.92) −0.13 (−1.77 to 1.50) −0.61 (−2.18 to 0.95)
*P < 0.05; **P < 0.01; ***P < 0.001. 1PSC: Physical summary component of the SF-36. 2MSC: Mental summary component of the SF-36.
Model 1: adjusted for age (60-69, 70-79, ≥ 80 years). Model 2: adjusted for age (60-69, 70-79, ≥ 80 years), physical activity (inactive, moder-
ate, regular/intense), BMI (normal weight, overweight, obesity), tobacco use (non-smoker, ex-smoker, smoker), alcohol consumption (never
drinker, ex-drinker, moderate consumption, excess consumption), coffee consumption (no consumption, < 1, 1-2, ≥ 2 cups/day), educational
level (no formal education, primary, secondary and university education), number of social ties, number of chronic diseases (0, 1, ≥ 2), depres-
sion, cognitive impairment, arousal from sleep at night, intake of anxiolytic medication.
Sleep Duration and Health-Related Quality of Life—Faubel et al
SLEEP, Vol. 32, No. 8, 2009 1065
higher prevalence of hypertension among women rather than
men.56 In contrast, in a large cohort of volunteers from the
American Cancer Society, the association between (short-dura-
tion) sleep and mortality was stronger in men than in women.57
Our study is unique because it covered a representative sam-
ple of the older adult population of a whole country, and includ-
ed a longitudinal follow-up. Moreover, it examined the impact
of sleep duration on a good number of different health dimen-
sions. Among its possible limitations is that sleep duration was
self-reported. Nevertheless, this variable correlates well with
objective actigraphic measurements.58 Moreover, sleep du-
ration in our study was similar to that reported in a previous
study on another representative sample of Spanish elderly.59 A
further limitation is that sleep duration in 2003 was not mea-
sured, which is important because we do not know the stability
of this variable over time or the induction time of the health
effects of sleep. Similarly, we did not asked about the reasons
for short-duration sleep (insomnia, work or family responsibili-
ties, watching nighttime television, lesser sleep need of certain
individuals) and for long-duration sleep (medication, greater
sleep need of certain individuals, absence of work or family
obligations), which could affect HRQL differently. Lastly, it is
possible that the results may not apply to populations having
sunlight exposures, lifestyle habits (e.g., diet, physical activ-
ity) and lifestyles (work and leisure timetables) other than those
of Mediterranean countries. Moreover, an association between
sleep duration and subsequent change in HRQL over a follow-
up longer than two years cannot still be ruled out.
Taking into account the above considerations, we conclude that
extreme sleep durations are a marker of worse HRQL in senior
also associated with poor HRQL. There is evidence that symp-
toms of insomnia, including difculty initiating and maintain-
ing sleep and daytime sleepiness, are associated with a decrease
in HRQL measured with the SF-36, in studies conducted among
older adults in the United States,45-48 Australia,49 Germany,50 and
Japan.51 There is also evidence from one clinical trial showing
that treatment of primary insomnia with a hypnotic improved
several scales on the SF-36 over six months.52 Lastly, disturbed
sleep, as measured by actigraphy and polysomnography, has
been associated with poorer physical function in older adults.53
Also, if the study relationship is causal, we would expect
the sleep duration to be associated with several health and so-
cial problems conceptually close to HRQL. Tworoger et al re-
ported that shorter sleep duration was associated with cognitive
impairment in cross-sectional analyses, but not over a 2-year
follow-up, among women 70 to 81 years in the Nurses’ Health
Study.33 Groeger et al found only minor differences in enjoy-
ment/satisfaction with life, success/achievement, and effort/
vital energy across categories of sleep duration in individuals
aged 16–96 years from Great Britain.54 Lastly, Bliwise et al
found no substantial associations between sleep duration and
several measures of disease and psychosocial function in sub-
jects between the ages of 50 and 65 years.55 Thus, data for co-
herence with previous epidemiologic knowledge are only fairly,
but not totally, compatible with a causal relationship between
sleep duration and HRQL.
Finally, it is not easy to understand why, in our study, the
associations varied with sex. Nevertheless, there are precedents
for sex differences in this research eld. For instance, in the
Whitehall II Study, short-duration sleep was associated with a
Table 4—Beta Regression Coefcients of the SF-36 Scores in 2001 According to Some Lifestyles and the Number of Chronic Diseases in
2001
  Physical Role- Bodily General Vitality Social Role- Mental PSC1 MSC2
functioning physical pain health functioning emotional health
Men
Age (years)3
70-79 −2.3 −3.2 −0.4 1.1 0.4 −0.8 1.9 0.8 −0.8 0.8
≥ 80 −13.5*** −6.1* −3.6 0.96 −2.9 −3.1 −1.7 1.7 −3.4*** 1.2
Physical activity3
Moderate 11.4*** 4.9* 4.6** 7.0*** 6.5*** 7.6*** 1.3 1.8 3.8*** 0.6
Regular/Intense 19.7*** 11.3* −1.5 16.5*** 16.4*** 14.3*** 4.8 8.8*** 5.9*** 3.7**
Intake of anxiolytic medication3 −6.9*** 9.8** −5.2* −7.2*** −6.2** −9.5*** −10.8*** −11.0*** −1.8* −5.0***
Number of diseases3
1 −5.6*** −7.3** −9.3*** −5.3*** −5.6*** −2.9* 0.9 −2.3* −3.4*** 0.05
≥ 2 −16.0*** −16.3*** −18.8*** −13.3*** −13.5*** −5.8*** −5.3** −7.5*** −7.4*** 1.5*
Women
Age (years)3
70-79 −5.1*** −2.5 −1.4 1.4 0.5 −0.2 −0.2 1.4 −1.2* 1.0
≥ 80 −19.6*** −11.2*** −0.8 2.4* −2.2 −2.9 −3.5 0.2 −4.1*** 1.2
Physical activity3
Moderate 14.0*** 7.4*** 8.0*** 6.4*** 7.6*** 10.4*** 5.1*** 2.7** 4.5*** 1.4**
Regular/Intense 19.3*** 1.8 14.0*** 12.0*** 13.8*** 8.9* 5.6 7.9** 5.7*** 2.7
Intake of anxiolytic medication3 −5.9*** −7.9*** −6.2*** −3.3*** −4.1*** −6.2*** −5.9*** −7.4*** −1.8*** −2.8***
Number of diseases3
1 −7.3*** −7.7*** −10.3*** −6.7*** −4.6*** −1.2 −3.6 −2.5* −3.6*** −0.2
≥ 2 −14.0*** −19.8*** −19.2*** −12.6*** −11.1*** −8.2*** −9.5*** −6.1*** −7.2*** −1.9**
*P < 0.05; **P < 0.01; ***P < 0.001. 1PSC: Physical summary score of the SF-36. 2MSC: Mental summary score of the SF-36. 3The reference
categories are: age < 69 years, normal weight, physically inactive, intake of anxiolytic medication (no), no disease diagnosed. Linear regression
adjusted for age, physical activity (inactive, moderate, regular/intense), BMI (normal weight, overweight, obesity), tobacco use (non-smoker,
ex-smoker, smoker), alcohol consumption (never drinkers, ex-drinker, moderate consumption, excess consumption), coffee consumption (no
consumption, < 1, 1-2, ≥ 2 cups/day), educational level (no formal education, primary, secondary and university education), number of social ties,
number of chronic diseases (0, 1, ≥ 2), depression, cognitive impairment, arousal from sleep at night, intake of anxiolytic medication.
Sleep Duration and Health-Related Quality of Life—Faubel et al
SLEEP, Vol. 32, No. 8, 2009 1066
Table 5—Beta Regression Coefcients (95% Condence Interval) of Change on the SF-36 Scores Between 2001 and 2003 According to
Usual Sleep Duration in 2001 Among Women
Sleep duration (hours per 24-hour period)
  ≤5 6 7 8 9 ≥10
N 167 181 211 347 214 199
Model 1
Physical functioning −4.69 (−9.07 to −0.31)* −1.07 (−5.32 to 3.19) Ref. 0.95 (−2.72 to 4.62) –2.21 (–6.28 to 1.87) –3.09 (–7.29 to 1.12)
Role-physical −0.87 (−8.29 to 6.54) 5.94 (–1.22 to 13.10) Ref. 4.17 (–2.00 to 10.33) 3.30 (–3.56 to 10.16) –4.82 (–11.86 to 2.23)
Bodily pain −3.45 (−8.92 to 2.01) 0.85 (–4.45 to 6.15) Ref. 3.66 (–0.91 to 8.22) –0.66 (–5.74 to 4.41) –0.14 (–5.35 to 5.07)
General health −4.84 (−8.37 to −1.31)** –0.34 (–3.77 to 3.09) Ref. 0.38 (–2.57 to 3.34) 0.67 (–2.62 to 3.96) 0.66 (–2.73 to 4.06)
Vitality −2.73 (−7.25 to 1.79) 0.51 (–3.89 to 4.90) Ref. –0.95 (–4.73 to 2.84) –0.82 (–5.03 to 3.38) –4.46 (–8.79 to –0.14)*
Social functioning −1.33 (−6.59 to 3.92) 0.60 (–4.51 to 5.72) Ref. 1.98 (–2.43 to 6.39) 0.10 (–4.80 to 5.01) –3.77 (–8.85 to 1.28)
Role-emotional −4.07 (−11.58 to 3.44) –1.16 (–8.49 to 6.17) Ref. 4.06 (–2.26 to 10.38) –2.13 (–9.14 to 4.89) –7.76 (–14.96 to –0.57)*
Mental health −2.61 (−6.77 to 1.55) –0.98 (–5.03 to 3.08) Ref. –1.04 (–4.54 to 2.46) –1.81 (–5.70 to 2.07) –3.41 (–7.40 to 0.58)
PSC1 −1.09 (−2.55 to 0.37) 0.41 (–1.01 to 1.83) Ref. 1.15 (–0.07 to 2.37) –0.04 (–1.39 to 1.32) –0.13 (–1.53 to 1.26)
MCS2 –0.99 (–3.19 to 1.20) –0.49 (–2.63 to 1.65) Ref. –0.02 (–1.87 to 1.83) –0.64 (–2.70 to 1.41) –2.60 (–4.71 to –0.49)*
Model 2
Physical functioning –3.57 (–7.96 to 0.81) –0.67 (–4.92 to 3.59) Ref. 1.56 (–2.07 to 5.19) –.85 (–4.93 to 3.23) –2.02 (–6.26 to 2.21)
Role-physical 0.56 (–6.86 to 7.99) 5.10 (–2.06 to 12.26) Ref. 4.11 (–2.01 to 10.22) 4.81 (–2.06 to 11.68) –2.19 (–9.30 to 4.93)
Bodily pain –2.01 (–7.47 to 3.46) 0.78 (–4.53 to 6.07) Ref. 3.69 (–0.84 to 8.21) 0.37 (–4.72 to 5.45) 0.47 (–4.79 to 5.74)
General health –2.99 (–6.51 to 0.53) 0.54 (–2.89 to 3.96) Ref. 0.88 (–2.05 to 3.80) 0.83 (–2.46 to 4.11) 1.05 (–2.36 to 4.46)
Vitality –1.03 (–5.53 to 3.47) 0.38 (–3.99 to 4.75) Ref. 0.09 (–3.64 to 3.82) –0.10 (–4.29 to 4.09) –3.58 (–7.92 to 0.77)
Social functioning 0.45 (–4.82 to 5.71) 0.38 (–4.74 to 5.50) Ref. 2.91 (–1.47 to 7.28) 1.64 (–3.27 to 6.56) –2.24 (–7.33 to 2.84)
Role-emotional –0.94 (–8.44 to 6.55) –0.45 (–7.75 to 6.84) Ref. 5.34 (–0.90 to 11.58) 0.69 (–6.31 to 7.69) –3.98 (–11.23 to 3.27)
Mental health –1.69 (–5.87 to 2.49) –1.34 (–5.40 to 2.73) Ref. –0.43 (–3.91 to 3.05) –1.11 (–5.01 to 2.79) –2.47 (–6.50 to 1.57)
PSC1 –0.56 (–2.01 to 0.89) 0.54 (–0.86 to 1.95) Ref. 1.31 (0.10 to 2.51) 0.37 (–0.98 to 1.72) 0.24 (–1.16 to 1.64)
MSC2 –0.15 (–2.34 to 2.05) –0.55 (–2.68 to 1.59) Ref. 0.42 (–1.41 to 2.25) –0.10 (–2.15 to 1.95) –1.80 (–3.92 to 0.32)
*P < 0.05; **P < 0.01. 1PSC: Physical summary component of the SF-36. 2MHS: Mental summary component of the SF-36. Model 1: adjusted
for age (60-69, 70-79, ≥ 80 years) and health-related quality of life in 2001. Model 2: adjusted for age (60-69, 70-79, ≥ 80 years), health-
related quality of life in 2001, physical activity (inactive, moderate, regular/intense), BMI (normal weight, overweight, obesity), tobacco
use (non-smoker, ex-smoker, smoker), alcohol consumption (never drinker, ex-drinker, moderate consumption, excess consumption), coffee
consumption (no consumption, < 1, 1-2, ≥ 2 cups/day), educational level (no formal education, primary, secondary and university educa-
tion), number of social ties, number of chronic diseases (0, 1, ≥ 2), depression, cognitive impairment, arousal from sleep at night, intake of
anxiolytic medication.
Table 6—Beta Regression Coefcients (95% Condence Interval) of Change on the SF-36 Scores Between 2001 and 2003 According to
Usual Sleep Duration in 2001 Among Men
Sleep duration (hours per 24-hour period)
  ≤5 6 7 8 9 ≥10
N  81 107 157 287 159 201
Model 1
Physical functioning 1.28 (–4.78 to 7.33) –0.38 (–5.93 to 5.16) Ref. 1.03 (–3.36 to 5.43) –2.82 (–7.81 to 2.16) –0.26 (–4.98 to 4.45)
Role-physical –15.8 (–26.0 to –5.62)** –6.58 (–15.88 to 2.72) Ref. –0.23 (–7.61 to 7.15) –13.64 (–22.10 to –5.27)** –9.94 (–17.85 to –2.03)*
Bodily pain –1.51 (–8.84 to 5.82) –8.22 (–14.92 to –1.52)* Ref. –1.39 (–6.73 to 3.95) –2.89 (–8.92 to 3.14) –0.52 (–6.23 to 5.19)
General health –0.55 (–5.71 to 4.61) 0.06 (–4.66 to 4.79) Ref. –0.55 (–4.30 to 3.19) –0.99 (–5.25 to 3.26) 0.55 (–3.47 to 4.58)
Vitality 3.06 (–3.25 to 9.38) –1.07 (–6.85 to 4.70) Ref. 1.87 (–2.72 to 6.45) –0.77 (–5.98 to 4.44) 2.13 (–2.79 to 7.05)
Social functioning –0.78 (–7.36 to 5.80) –5.37 (–11.39 to 0.64) Ref. 4.06 (–0.71 to 8.84) 0.02 (–5.40 to 5.43) –2.75 (–7.86 to 2.36)
Role-emotional –6.90 (–16.22 to 2.41) –5.57 (–14.08 to 2.94) Ref. –1.46 (–5.29 to 8.22) –4.43 (–12.09 to 3.23) –3.25 (–10.49 to 3.99)
Mental health 0.98 (–4.56 to 6.53) –2.00 (–7.07 to 3.07) Ref. 1.42 (–2.60 to 5.45) –2.67 (–7.23 to 1.89) 0.90 (–3.41 to 5.21)
PSC1 0.11 (–1.81 to 2.04) –1.09 (–2.85 to 0.67) Ref. 0.04 (–1.36 to 1.43) –0.64 (–2.22 to 0.94) –0.03 (–1.53 to 1.46)
MCS2 –0.74 (–3.54 to 2.06) –1.55 (–4.11 to 1.00) Ref. 1.17 (–0.86 to 3.20) –1.05 (–3.36 to 1.25) –0.42 (–2.59 to 1.76)
Model 2
Physical functioning −1.49 (−4.63 to 7.60) –0.23 (–5.90 to 5.44) Ref. 0.81 (–3.64 to 5.24) –2.00 (–7.07 to 3.06) 0.38 (–4.50 to 5.26)
Role-physical −14.92 (−25.17 to –4.67)** –4.14 (–13.63 to 5.36) Ref. –0.27 (–7.71 to 7.17) –10.41 (–18.89 to –1.92)* –5.22 (–13.40 to 2.96)
Bodily pain –0.88 (–8.20 to 6.44) –5.95 (–12.74 to 0.84) Ref. –0.93 (–6.28 to 4.41) –-1.03 (–7.10 to 5.05) 2.30 (–3.59 to 8.19)
General health –0.36 (–5.60 to 4.89) 0.41 (–4.44 to 5.27) Ref. –1.04 (–4.84 to 2.77) –-0.92 (–5.26 to 3.42) –0.14 (–4.33 to 4.04)
Vitality 4.08 (–2.22 to 10.38) 0.40 (–5.44 to 6.25) Ref. 1.03 (–3.55 to 5.61) –-0.20 (–5.43 to 5.03) 2.28 (–2.76 to 7.31)
Social functioning –0.64 (–7.23 to 5.96) –3.43 (–9.55 to 2.68) Ref. 3.07 (–1.72 to 7.86) 1.12 (–4.34 to 6.59) –1.34 (–6.61 to 3.92)
Role-emotional –3.95 (–13.36 to 5.45) –3.00 (–11.70 to 5.69) Ref. 2.03 (–4.79 to 8.84) –3.06 (–10.83 to 4.71) –0.35 (–7.86 to 7.15)
Mental health 1.09 (–4.50 to 6.69) –0.77 (–5.96 to 4.42) Ref. 1.01 (–3.05 to 5.08) –2.19 (–6.83 to 2.45) 2.29 (–2.18 to 6.76)
PSC1 0.25 (1.69 to 2.19) –0.75 (–2.55 to 1.05) Ref. –0.02 (–1.43 to 1.40) –0.28 (–1.89 to 1.33) 0.27 (–1.28 to 1.82)
MSC2 –0.27 (–3.09 to 2.55) –0.72 (–3.34 to 1.89) Ref. 0.97 (–1.08 to 3.01) –0.73 (–3.07 to 1.60) 0.28 (–1.97 to 2.53)
*P < 0.05; **P < 0.01. 1PSC: Physical summary component of the SF-36. 2MSC: Mental summary component of the SF-36. Model 1: adjusted
for age (60-69, 70-79, ≥ 80 years) and health-related quality of life in 2001. Model 2: adjusted for age (60-69, 70-79, ≥ 80 years), health-
related quality of life in 2001, physical activity (inactive, moderate, regular/intense), BMI (normal weight, overweight, obesity), tobacco
use (non-smoker, ex-smoker, smoker), alcohol consumption (never drinker, ex-drinker, moderate consumption, excess consumption), coffee
consumption (no consumption, < 1, 1-2, ≥ 2 cups/day), educational level (no formal education, primary, secondary and university educa-
tion), number of social ties, number of chronic diseases (0, 1, ≥ 2), depression, cognitive impairment, arousal from sleep at night, intake of
anxiolytic medication.
Sleep Duration and Health-Related Quality of Life—Faubel et al
SLEEP, Vol. 32, No. 8, 2009 1067
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citizens. Our results, however, should be interpreted with caution,
given the very short follow-up time and the lack of follow-up
data for sleep duration. Moreover, we have observed a sex differ-
ence in the study association, which was not anticipated. Because
of it and the incomplete fulllment of several causality criteria in
epidemiology, we are still far from establishing that sleep dura-
tion is causally related to HRQL. As this is one of the rst stud-
ies of its kind in older adults, its results should be conrmed in
future studies. Furthermore, advance in this eld requires a better
knowledge of the biologic and social mechanisms underlying the
relationship between sleep duration and health.
ACKNOWLEDGMENTS
This study was funded by FIS grant 06/0366. Raquel Faubel
had a fellowship (Programa de Formación de Profesorado
Universitario) from the Ministry of Education and a grant from
the Madrid City Council in the “Residencia de Estudiantes.”
Esther López-García had a “Ramón y Cajal” contract from the
Ministry of Education. The funding bodies had no role in data
extraction and analysis, writing of the manuscript, or in the de-
cision to submit the paper for publication.
DISCLOSURE STATEMENT
This was not an industry supported study. The authors have
indicated no nancial conicts of interest.
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Sleep Duration and Health-Related Quality of Life—Faubel et al
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... However, since sleep duration (quality) and HRQoL will decrease with age, so they may be less representative for the elderly. Additionally, the vast majority of studies only focus on the sleep duration [13,17] and draw inconsistent conclusions [16,20,21]. Last but not least, few studies have explored the pathway mechanism of HRQoL decline caused by sleep disorders. ...
... These findings are expected to contribute to the development of targeted interventions to improve HRQoL among elderly individuals in the United Kingdom. The association between sleep disorders and HRQoL among the elderly has been widely explored in China [14,16], Spain [17], and other countries [18,19]. However, due to differences in race, sample size, HRQoL instruments selected, and potential confounders, our study is slightly different from them. ...
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... Possible cause of altered sleep patterns can be changes in circardian rhythm in old age. (1,2,4,5) Insufcient duration and poor quality of sleep causes alterations in sympathovagal balance and increase in sympathetic drive. This results into insulin resistance and impaired glucose metabolism which increases risk of diabetes mellitus. ...
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Introduction: Due to changes in circadian rhythm geriatric population struggles to get enough sleep. Also there is increase in risk of diabetes and hypertension with increasing age. To nd out correlation between 'durationObjectives: and quality' of sleep and incidence of 'diabetes mellitus (DM) and hypertension' in geriatric population staying at old age home and home. To compare geriatric population staying at old age home with geriatric population staying at home. It was an analyticalMaterials And Methods: observational study done in 50 subjects of geriatric age group of 65-75years, 25 subjects staying at old age home (Group A) and 25 subjects staying at home (Group B) were examined by using sleep questionnaire. DM was reported in 76% with short duration and 84% withResults: disturbed sleep in total geriatric population. For Group A DM was reported in 75% with short duration and 82% with disturbed sleep. For Group B DM was reported in 77% with short duration and 85% with disturbed sleep. Hypertension was reported in 75% with short duration and 81% with disturbed sleep in total geriatric population. For Group A hypertension was reported in 71% with short duration and 79% with disturbed sleep. For Group B hypertension was reported in 79% with short duration and 85% with disturbed sleep. Due to sympathovagal imbalanceDiscussion: there is insulin resistance, impaired glucose metabolism and obesity which manifests into DM in short duration disturbed sleep. Also insufcient sleep causes increased sympathetic activity, increased stress hormones and lack of nocturnal dipping in blood pressure which is responsible for prevalence of hypertension. Prevalence of DM and Hypertension is more in geriatric population with short disturbed sleep. There isConclusion: no signicant difference in prevalence of DM and hypertension in Group A and Group B
... These studies find that poor sleep quality and extreme sleep duration (both short and long) are associated with low HRQoL. In addition, three previous studies conducted in the US, Spain, and Korea also find a U-shape association between sleep duration and HRQoL [18][19][20]. However, the combined effect of sleep quality and night sleep duration on HRQoL remains unclear, especially in resourcelimited countries and areas. ...
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Background: The combined effect of sleep quality and night sleep duration on health-related quality of life (HRQoL) remains unclear, especially in resource-limited countries and areas. This study aimed to explore the independent and combined effects of sleep quality and night sleep duration on HRQoL. Methods: A total of 21,926 eligible participants from the Henan rural cohort study were selected. The Pittsburgh Sleep Quality Index was utilized to evaluate sleep quality and night sleep duration. The Tobit regression model, generalized linear model (GLM), and logistic regression model were performed to assess the associations of sleep quality and night sleep duration with HRQoL. The restricted cubic spline was applied to identify the dose-response relationships of sleep quality and night sleep duration with HRQoL. Results: After multivariable adjustment, the Tobit regression and GLM indicated that the regression coefficients [95% confidence interval (CI)] for poor sleep quality were - 0.124 (- 0.133, - 0.114) and - 6.25 (- 6.71, - 5.78) on utility index and VAS score, respectively. Compared with the reference group (7 h-), participants with short sleep duration (< 6 h) or long sleep duration (≥10 h) reported a lower HRQoL. A U-shape relationship between night sleep duration and HRQoL was observed, along with a J-shape relationship between sleep quality and HRQoL (P for non-linear < 0.001). Furthermore, individuals with longer night sleep duration (≥10 h) and poorer sleep quality were strongly associated with lower HRQoL (utility index [odds ratio (OR) (95% CI)]: 6.626 (3.548, 8.920), VAS score [OR (95% CI)]: 2.962 (1.916, 4.578)). Conclusion: Poor sleep quality and extreme night sleep duration were independently and combinedly associated with low HRQoL, suggesting that maintaining good sleep quality and appropriate night sleep duration was important. Clinical trial registration: The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 06 July, 2015. http://www.chictr.org.cn/showproj.aspx?proj=11375 .
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International studies have demonstrated associations between sleep problems and poor psychological well-being; however, Canadian data are limited. This study investigated this association using cross-sectional baseline data from the Canadian Longitudinal Study on Aging, a national survey of 30,097 community-dwelling adults, 45–85 years of age. Short sleep duration, sleep dissatisfaction, insomnia symptoms, and daytime impairment were consistently associated with a higher prevalence of dissatisfaction with life, psychological distress, and poor self-reported mental health. Long sleep duration was associated with a higher prevalence of psychological distress and poor self-reported mental health, but not with dissatisfaction with life. Associations between sleep problems and psychological distress were 11–18 per cent stronger in males. With each 10-year increase in age, the association between daytime impairment and life dissatisfaction increased by 11 per cent, and insomnia symptoms and poor mental health decreased by 11 per cent. Sleep problems in middle-aged and older adults warrant increased attention as a public health problem in Canada.
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PurposeThis study investigated the optimal total sleep duration per day required by collegiate athletes to maintain the physical and mental health-related quality of life (HRQOL), compared with non-athlete students.Methods In this cross-sectional study, a questionnaire survey was conducted to assess demographic variables, lifestyle and sleep habits, and HRQOL in 392 collegiate students (non-athletes, n = 174; athletes, n = 218). Physical component summary (PCS) and mental component summary (MCS) were assessed using the short-form-8 health survey. Participants with both good PCS and MCS were defined as having a good HRQOL. To confirm an association between the total sleep duration per day and good HRQOL, logistic regression analyses were conducted in non-athlete students and collegiate athletes separately. Subsequently, receiver-operating curve (ROC) analyses were performed for the detection of the cut-off point of total sleep duration per day sufficient to maintain a good HRQOL.ResultsThe average total sleep duration per day was 7 h 19 min for collegiate athletes, and 78.9% of them had a worse PCS. The cut-off point of total sleep duration per day to maintain good HRQOL for collegiate athletes was 7.92 h (area under ROC, 0.64; P = 0.038; sensitivity, 75.4%; specificity, 57.9%), which was longer than 6.79 h for non-athlete students.Conclusion Collegiate athletes required longer nocturnal sleep than non-athlete students. Nevertheless, their habitual nocturnal sleep duration was shorter compared to their optimal duration; around 70% of them faced chronic insufficient sleep. Improving sleep habits and sleep education is important in maintaining their good health-related quality of life.
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Background Quantifying the effect of depression on sleep duration is of great importance to the diagnosis, control, prevention of sleep-related diseases and understanding related biological mechanisms. However, existing studies explored the effect without considering depressive duration, which may cause inaccurate results. Methods Accessing the data from the China Health and Retirement Longitudinal Study in 2011, 2013, 2015 and 2018, we used the interval between two interviews with persistent depression status to approximate depressive duration. Five analysis subsamples with different depressive durations, i.e., 2, 3, 4, 5, 7 years, were obtained. The change amount of sleep duration between two interviews was used as the outcome variable. A multiple linear model was independently used to estimate the effect in each subsample, and meta-regression was used to test the trend. Subgroup analyses in terms of genders, ages and baseline sleep durations were performed. Results On average, 2, 3, 4, 5, 7-years depressive durations significantly reduced sleep duration by 0.46, 0.57, 0.72, 0.75, 1.07 h (P < 0.001), respectively. Especially for the elderly, female, and participants with normal baseline sleep duration, the reduction was larger. Trend test showed that the variation trend was significant (P < 0.001). Similar results were found in the subgroup analyses. Limitations Sleep duration and depression are not measured by gold-standard methods. Conclusions Depression significantly reduces sleep duration, especially for the elderly, female, and people with normal baseline sleep duration. Longer depressive duration reduces sleep duration more. Such finding provides more detailed epidemiological evidence for depression-sleep relationship.
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V monografiji avtorice predstavljajo ugotovitve več raziskav, ki so jih izvedle v zadnjih desetih letih, in jih umestijo na področje pozitivne psihologije, ki se je kot znanstvena disciplina uveljavila po letu 2000. Kot teoretični okvir v prvem poglavju predstavijo raziskave laičnega pojmovanja sreče in teoretične modele subjektivnega blagostanja. Poudarek na znanstveni ustreznosti merskih instrumentov v pozitivni psihologiji je spodbudil interes za konstrukt subjektivnega blagostanja tudi na drugih področjih psihologije.
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Objective This study examines the influence of the interview method (telephone or face-to-face in households) on the assessment of health behaviors and preventive practices. Material and method The same questionnaire was completed by two independent samples of the population aged 18-64 years living in the municipality of Madrid. One sample (n = 1,391 subjects) completed the questionnaire by telephone interview and the other (n = 739) by face-to-face interview in households. The results of the two samples for 28 variables related to anthropometry, physical activity, food consumption, tobacco and alcohol use, preventive practices and injuries were compared. Results The telephone sample had a higher rate of failed contact (31.8% vs. 22.2%) but a greater degree of cooperation than the sample for the face-to-face interview (83.0% vs. 74.0%). In total, 19 of the 28 variables showed a relative variation of less than 10% between the two surveys; the differences found were between 10 and 20% for eight variables and were higher than 20% for one variable. Differences were statistically significant for only four variables (sedentary leisure time, consumption of vegetables, giving up smoking and cholesterol measurement), with a relative variation of 6.1% (p < 0.01), 10% (p < 0.001), 36.7% (p < 0.01) and 8.6% (p < 0.01), respectively. The total cost of the telephone interview was half that of the face-to-face household interview. Conclusions The results of both surveys were very similar. Because of its lower cost, the telephone interview is a good option in public health research when data collection by interview is required.
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• Prospective epidemiologic data of the American Cancer Society disclosed that reported usual sleep durations among groups who complained of insomnia and sleeping pill use "often" overlapped with those of groups who had no complaints. Reports of insomnia were not consistently associated with increased mortality when several factors were controlled; however, men who reported usually sleeping less than four hours were 2.80 times as likely to have died within six years as men who reported 7.0 to 7.9 hours of sleep. The ratio for women was 1.4.8. Men and women who reported sleeping ten hours or more had about 1.8 times the mortality of those who reported 7.0 to 7.9 hours of sleep. Those who reported using sleeping pills "often" had 1.5 times the mortality of those who "never" used sleeping pills. These results do not prove that mortality could be reduced by altering sleep durations or by reducing hypnotic prescribing. Rather, studies are needed to determine the causes of these mortality risk factors.
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With suitable pharmacotherapy, patients with any degree of restless legs syndrome (RLS) should be able to obtain substantial relief of symptoms. The best therapeutic success is attained when the physician tailors therapy to the patient’s specific symptoms and can flexibly try a variety of agents, if needed. Therapy should be reserved for those in whom RLS cannot be managed with just sleep hygiene and related practices. It should not be withheld, however, if a patient reasonably believes that his or her quality of life is being impaired by RLS. The optimal initial approach to RLS in the general patient is usually the use of a dopaminergic agent: low-dose levodopa in milder cases, a dopamine agonist in more severe ones. Patients whose problems are primarily sleep related can initially be treated with a benzodiazepine. Patients who have symptoms primarily while awake can initially be treated with a dopaminergic agent or an opioid. Patients whose RLS discomfort is truly painful can initially be treated with gabapentin. Combination therapy with two or three agents from different classes can be useful as well. Determination of iron status is the most important initial laboratory evaluation in patients with RLS. Iron supplementation should be used as indicated. In the future, delivery modes other than oral administration of medications may be of significant benefit, especially in more severe cases.
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Fundamento Y Objetivo El Cuestionario de Salud SF-36 es el más usado en la bibliografía internacionalpara medir la calidad de vida relacionada con la salud. Los valores de referencia del cuestionario sonnecesarios para interpretar sus resultados en estudios clínicos y poblacionales. Un estudio realizadoen 1996 proporcionó dichos valores para la población española, pero no se desagregaron por edad enlos sujetos de 75 y más años, a pesar de que el estado de salud cambia al envejecer en los que, cadadía con más frecuencia, superan dicha edad. Además, el estado de salud de los ancianos de los paísesdesarrollados ha mejorado en los últimos años. Por ello, el objetivo de este trabajo ha sido obtenerlos valores de referencia del Cuestionario de Salud SF-36 en el año 2001 para la población españolaen grupos quinquenales de edad en el intervalo de 60 a 85 y más años. Sujetos Y Método Estudio transversal en una muestra de 3.949 personas representativas de la poblaciónespañola no institucionalizada de 60 y más años de edad. El Cuestionario de Salud SF-36 secompletó mediante entrevista personal en los domicilios. Se calcularon medidas de tendencia centraly de dispersión, y los percentiles de las puntuaciones de las 8 escalas del cuestionario, según la edady el sexo. Además se examinó la consistencia o fiabilidad interna de cada escala mediante el coeficientealfa de Cronbach. Resultados Los sujetos refirieron las puntuaciones más elevadas para las escalas de rol emocional(media [DE]: 84,8 [32,9]), función social (79,2 [28,0]) y rol físico (73,3 [41,1]). Los valores mediosde todas las escalas fueron superiores (mejor salud percibida) en los varones que en las mujeres (p < 0,0001). Al aumentar la edad disminuía la puntuación media en todas las escalas (p para la tendencialineal < 0,001) excepto la de salud mental (p para la tendencia lineal = 0,29 en mujeres; p parala tendencia lineal = 0,14 en varones), aunque el descenso fue mayor en las de función física y rol físico.La consistencia interna de todas las escalas fue muy alta (alfa de Cronbach de 0,84 a 0,95). Losresultados fueron similares a los obtenidos en el estudio de 1996. Conclusiones Estos resultados complementan los del estudio de 1996 y favorecerán la interpretaciónde los valores del Cuestionario de Salud SF-36 en estudios clínicos y poblacionales en personas de 60y más años en España. Background and Objective The SF-36 Health Survey questionnaire is the most widely used instrumentto measure health-related quality of life. Reference measures are needed to interpret its results in clinicaland population studies. In 1996, a study provided population-based norms for Spain, but thesewere not disaggregated by age in subjects aged 75 years and over, even though health status changeswith aging among those who overpass such age. Moreover, health status in elderly people from developedcountries has improved over the last years. This study obtains population-based norms for theSpanish version of the SF-36 Health Survey in five-year age-groups for those aged 60 to 85 and over. Subjects and Method Cross-sectional survey on a sample of 3,949 non-institutionalised subjects representativeof the Spanish population aged 60 years and over. Information on the SF-36 Health Survey wasobtained through house-hold personal interviews. Central position and dispersion statistics, as well aspercentiles, were calculated for each of the eight SF-36 scales by age and sex. Cronbach's alpha coefficientswere calculated to assess the internal reliability of each scale. Results Subjects reported higher scores for emotional role (mean [SD] 84.8 [32.9]), social functioning(79.2 [28.0]) and physical role (73.3 [41.1]). For all scales, mean scores were higher (better perceivedhealth) among men than women (p < 0.0001). As age increased, mean scores in all scales decreased(p for linear trend < 0.001) except for mental health (p for linear trend = 0.29 in women, p forlineal trend = 0.14 in men), yet the decrease was greater for physical functioning and physical role.Reliability was very high for all scales (Cronbach's alpha from 0.84 to 0.95). Results were similar tothose of the study carried out in 1996. Conclusions These results extend those obtained in 1996 and facilitate the interpretation of the SF-36Health Survey values in clinical and population studies in the Spanish population aged 60 years andolder.
Article
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.