SHORT SLEEP DURATION AND CENTRAL OBESITY IN WOMEN
Associations between Short Sleep Duration and Central Obesity in Women
Jenny Theorell-Haglöw, PhD1; Christian Berne, PhD2; Christer Janson, PhD1; Carin Sahlin, PhD3; Eva Lindberg, PhD1
Department of Medical Sciences, Respiratory Medicine and Allergology, and 2Department of Medical Sciences, Internal Medicine, Uppsala University,
Sweden; 3Department of Respiratory Medicine, Umeå University, Sweden
1
Study Objectives: The aim was to assess associations between sleep duration, sleep stages, and central obesity in women.
Design: Cross-sectional study.
Setting: City of Uppsala, Sweden.
Participants: Population-based sample of 400 women (range 20-70 years).
Interventions: Full-night polysomnography and measurement of anthropometric variables.
Measurements and Results: Sleep duration was inversely related to both waist circumference and sagittal abdominal diameter. Sleep duration
remained inversely related to waist circumference (adj. β = −1.22 cm/h; P = 0.016) and sagittal abdominal diameter (adj. β = −0.46 cm/h; P = 0.001)
after adjusting for potential confounders. Duration of slow wave sleep (SWS, adj. β = −0.058 cm/min; P = 0.025) and REM sleep (adj. β = −0.062
cm/min; P = 0.002) were both inversely related to waist circumference after adjustments. Moreover, duration of REM sleep was inversely related to
sagittal abdominal diameter (adj. β = −0.021 cm/min; P < 0.0001). These associations were stronger in young women (age < 50 years).
Conclusion: An inverse relationship between short sleep duration and central obesity was found in women after adjusting for confounders. Loss
of SWS and REM sleep may be important factors in the association between sleep loss and central obesity.
Keywords: Sleep duration, sleep stages, central obesity, women, population-based
Citation: Theorell-Haglöw J; Berne C; Janson C; Sahlin C; Lindberg E. Associations between short sleep duration and central obesity in women.
SLEEP 2010;33(5): 593-598.
SLEEP DURATION IN THE GENERAL POPULATION HAS
DECREASED FROM 8.5 H TO 7.2 H OVER THE LAST
30 YEARS.1,2 IN ADDITION, SLEEP COMPLAINTS ARE
common, especially in women.3 Parallel to the decrease in sleep
duration, the prevalence of obesity has increased, with several
studies finding associations between the two conditions.4-7 An
inverse relationship between self-reported sleep duration and
obesity has been found in adult men and women, as well as in
children.8 Short sleep duration has also been found to predict
weight gain and obesity later in life.5,6
Previous studies have primarily focused on self-reported
sleep duration in relation to obesity.4-7,9-13 Self-reported sleep is
a subjective measure in contrast to polysomnography, which allows for detailed analysis of sleep quantity and quality. Further,
earlier studies have examined the association between sleep and
body mass index (BMI), whereas the association between sleep
and central obesity is less clear. Central obesity is a stronger
risk factor than BMI for cardiovascular disease, type 2 diabetes mellitus,14 and mortality.15 Therefore, finding the underlying
causes of central obesity and potentially modifiable risk factors is important. Recently, an association between measured
sleeping time and waist circumference in elderly men has been
reported,16 but no data are available for women or younger
populations. Furthermore, the role of sleep architecture is less
clear. The aim of this study was therefore to use polysomnog-
raphy to analyze potential associations between sleep duration,
sleep stages, and central obesity in a population-based sample
of women aged 20-70 years. By analyzing measured sleep duration and time spent in different sleep stages with polysomnography, this study may enhance our knowledge about the
relationships between sleep duration, sleep stages, and central
obesity in women.
METHODS
The two-phased, population-based study “Sleep and Health
in Women” was conducted between 2000 and 2004. In the first
phase, randomly selected women (aged ≥ 20 years) from the
population registry of the city of Uppsala, Sweden were sent
a questionnaire on sleep disturbances and somatic disorders.
A total of 7,051 women responded, giving a response rate of
71.6%. Based on their response to a question on snoring, the
participants were categorized into non-snorers (n = 6,515) and
snorers (n = 518). In the second phase of the study a sample of
400 women, aged < 70 years (n = 6,112), were selected from
the responders in the first phase. Of the 400 women, 230 were
selected randomly from the snorers and 170 were selected randomly from the whole group. Such a sampling scheme was employed because one aim of the project “Sleep and Health in
women” was to study the association between sleep-disordered
breathing and glucose metabolism. Both phases of the study
have been described in detail previously.17,18 A flow chart of the
study design is depicted in Figure 1.
The women filled in questionnaires that included questions
on somatic disease, medication, snoring, daytime sleepiness,
physical activity, tobacco use, and alcohol consumption. The
participants’ physical activity was analyzed by 4 questions adopted from a questionnaire used in a large population-based
study on the relationship between physical activity and mortality in women.19 Based on the responses from 6 questions assessing smoking habits,18 the participants were categorized as
A commentary on this article appears in this issue on page 573.
Submitted for publication June, 2009
Submitted in final revised form January, 2010
Accepted for publication January, 2010
Address correspondence to: Jenny Theorell-Haglöw, Department of Medical Sciences, Respiratory Medicine and Allergology, Uppsala University,
Akademiska sjukhuset, SE- 751 85 Uppsala, Sweden; Tel: +46 18 611 02
42; Fax: +46 18 611 02 28; E-mail: jenny.theorell-haglow@medsci.uu.se
SLEEP, Vol. 33, No. 5, 2010
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Sleep Duration and Central Obesity—Theorell-Haglöw et al
age number of apneas and hypopneas per hour of sleep) was
calculated. Apnea was defined as complete cessation of nasal
and oral airflow lasting ≥ 10 sec, while hypopnea was defined
as a reduction in airflow of ≥ 50% compared with baseline in
combination with ≥ 3% reduction in oxyhaemoglobin saturation or an arousal.
In the morning following the polysomnography the women
returned to the laboratory where a research nurse measured
height, weight, and central obesity (waist circumference and
sagittal abdominal diameter). BMI was calculated as body mass
(kg) divided by height (m) squared (kg/m2). Waist circumference was measured at standing, and the sagittal abdominal
diameter was measured lying down with the back against the
surface beneath.21 Both waist circumference and sagittal abdominal diameter were measured midway between the lower
rib margin and the anterior superior iliac crest at the end of
normal exhalation. A waist circumference ≥ 88 cm was used to
define central obesity according to National Cholesterol Education Program (NCEP) criteria.22
Statistical Analyses
Statistical analyses were performed using Stata 9.0 (Stata
Corporation, College Station, TX, USA). Univariate analyses
were conducted using the unpaired t-test or the χ2 test to compare baseline data between groups. Associations between sleep
duration and measures of obesity were further analyzed using
multiple regression analysis. Results from the regression analysis are presented as adjusted estimated β-values with P-values.
Statistically significant differences were assumed when P < 0.05.
Based on previous analysis of this female population,18 at least
94% of the women who were 46 years of age were classified as
being premenopausal, whereas at least 93% of the women 53
years of age were considered postmenopausal. Therefore, when
analyzing the influence of age in the present study, the cut-off
point was set at 50 years. Interaction analyses were conducted
to detect significant differences in the association between sleep
duration and age (dichotomized as ≥ 50 years and < 50 years).
Interaction analyses were also conducted to detect significant
differences in the association between sleep duration and the
2 measures of central obesity in women with and without obstructive sleep apnea (AHI ≥ 15 and < 15, respectively and AHI
≥ 5 and < 5, respectively). A P-value < 0.05 was considered
indicating interaction.
The study was approved by the Ethics Committee of the
Medical Faculty at Uppsala University and all participants gave
their informed consent before participating.
Figure 1—Flow chart of the study design
“current smokers,” “ex-smokers,” or “non-smokers.” Alcohol
consumption was assessed by a question requiring details of the
weekly consumption of alcoholic beverages. From the response
to this question, the total amount of alcohol in grams per week
was calculated.
All 400 women underwent a whole night polysomnography
using the ambulatory system EMBLA (Flaga Inc., Reykjavik,
Iceland). Sleep stages were assessed using electroencephalography, electrooculography and submental electromyography.
Continuous measurement of nasal air pressure, oral and nasal
airflow, thoracic and abdominal respiratory movement, and
oxyhemoglobin saturation was conducted to assess sleep disordered breathing. Electrodes and sensors for the recordings were
attached to the participant and connected to the recording system at the sleep laboratory in the evening preceding the polysomnography. All recordings were performed in the women’s
home, except in 6 cases, where the women slept at the hospital’s
patient hotel. The participants were free to choose when to go
to bed and wake up. Data were downloaded to the Somnologica
reviewing analysis software (Version 2.0, Flaga Inc., Reykjavik, Iceland) and sleep was scored manually in 30-sec epochs
according to standard criteria.20 The polysomnographic recording was considered acceptable when there were ≥ 4 h of sleep
recorded and no registration had been lost for ≥ 20 min of the
night. Six polysomnography recordings were repeated because
of poor quality of the first recording. Total sleep time (TST),
amounts of different sleep stages (in minutes and percent), and
sleep efficiency (i.e., the ratio of TST to the amount of time
spent in bed) were collected from the polysomnography information. In addition, the apnea-hypopnea index (AHI; the averSLEEP, Vol. 33, No. 5, 2010
RESULTS
Seven hundred thirty-seven women were asked to participate in the second phase of “Sleep and Health in Women,” and
400 accepted. The reasons for refusing participation were: lack
of time (14.9%), ill or pregnant (7.5%), technical reasons or
language difficulties (3.6%), not willing (45.4%), and reasons
unknown (28.7%). The non-responders were younger (43.8 ±
14.1 y [mean ± SD] versus 47.2 ± 11.3 y; P = 0.0003) than the
responders. They also had lower BMI (24.9 ± 4.6 kg/m2 versus
25.8 ± 4.7 kg/m2; P = 0.009) and were more often physically
inactive (23% versus 16%; P = 0.038), compared with responders. There was no difference in self-reported sleep duration
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Sleep Duration and Central Obesity—Theorell-Haglöw et al
Table 1—Characteristics of the study populationa
Table 2—Associations between total sleep time and measures of central
obesity after adjustment for potential confoundersa,b
Central obesity
(NCEP criteriab)
Yes (n = 182) No (n = 218)
Age (years)
53.0 ± 9.7
47.7 ± 11.9
< 0.0001
Total sleep time (minutes)
372.3 ± 73.9
397.2 ± 65.3
0.0004
Slow wave sleep (minutes)
33.7 ± 22.9
40.8 ± 22.8
0.002
REM sleep (minutes)
63.2 ± 29.5
77.5 ± 28.9 < 0.0001
Sleep efficiency (%)
82.2 ± 13.1
87.5 ± 9.9
< 0.0001
Apnea-hypopnea index
18.8 ± 19.0
9.1 ± 9.7
< 0.0001
Body mass index (kg/m2)
30.4 ± 4.7
23.5 ± 2.4
< 0.0001
Sagittal abdominal diameter 23.5 ± 0.21
(centimeters)
Level of physical activity
High
Medium
Low
Smoking
Non-smoker
Ex-smoker
Current smoker
Alcohol consumption
(grams/week)
a
b
18.7 ± 0.14 < 0.0001
55.8 ± 58.0
54.9 ± 58.5
Adj.
β-value P-value
−1.24
0.016
−0.46
0.001
Slow wave sleep (minutes) −0.058
0.025
−0.013
0.068
Slow wave sleep (%)
−0.20
0.050
−0.034
0.21
REM sleep (minutes)
−0.062
0.002
−0.021
< 0.0001
REM sleep (%)
−0.15
0.074
−0.057
0.013
Sleep efficiency (%)
−0.13
0.014
−0.043
0.003
0.11
0.069
0.037
0.020
0
3.21
10.95
0.045
< 0.0001
0
1.34
3.39
0.002
< 0.0001
0
1.06
1.29
0.43
0.41
0
−0.12
−0.10
0.73
0.81
Alcohol consumption
(grams/week)
0.0061
0.55
Apnea-hypopnea index
2.53
Exercise level
High
Medium
Low
0.12
109 (50.7)
65 (30.2)
41 (19.1)
Adj.
β-value P-value
Age (years)
48 (22.5)
151 (70.9)
14 (6.6)
72 (40.5)
63 (35.4)
43 (24.2)
Sagittal
abdominal diameter
(cm)
Total sleep time (hours)
< 0.0001
18 (10.1)
127 (71.0)
34 (19.0)
Waist
circumference
(cm)
P-value
Smoking
Non-smoker
Ex-smoker
Currentsmoker
0.90
Results are presented as mean ± SD or n (%).
Waist circumference ≥ 88 cm
< 0.0001
0.0008
0.59
0.77
< 0.0001
Results are presented as adjusted estimated β-values with P-values.
β-values are adjusted for age, level of physical activity, smoking status,
alcohol consumption, and apnea-hypopnea index.
a
b
(7.0 ± 1.2 h versus 6.9 ± 1.2 h; P = 0.39), smoking (26% versus
23%; P = 0.37), or presence of somatic disease (37% versus
39%; P = 0.58) between responders and non-responders.
The centrally obese women (waist circumference ≥ 88 cm)
in the study were older, had higher BMI, and had a lower level
of physical activity than women without central obesity (Table
1). In addition, the centrally obese women had shorter sleep
duration, less sleep efficiency, less slow wave sleep (SWS),
less REM sleep, and higher AHI. The two groups did not differ
significantly in either smoking status or alcohol consumption
(Table 1). No difference in sleep efficiency was observed between the women randomly selected from the snoring group
in Phase I and women selected from the whole group (85.9% ±
13.1% versus 84.6% ± 10.7%; P = 0.26).
A significant negative association was observed between
TST and waist circumference, and TST and sagittal abdominal
diameter in unadjusted data. There was a mean difference of
9 cm in waist circumference and 3 cm in sagittal abdominal
diameter between women sleeping < 5 h and women sleeping
≥ 8 h (Figure 2).
No interactions were detected between the selection group
from Phase I (snorer or from the whole group) and any of the
variables of sleep when using waist circumference (P for interaction = 0.18-0.97) or abdominal sagittal diameter (P for interaction = 0.35-0.80) as the dependent variable. Furthermore,
no interactions were observed between AHI (≥ 15 and < 15)
and TST when using waist circumference (P = 0.25) or sagittal
abdominal diameter (P = 0.30) as the dependent variable. This
SLEEP, Vol. 33, No. 5, 2010
Figure 2—Waist circumference and sagittal abdominal diameter in
relation to sleep duration. Results are presented as mean ± SE. The box
indicates the limit for central obesity according to National Cholesterol
Education Program (NCEP) criteria.22
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Sleep Duration and Central Obesity—Theorell-Haglöw et al
There was a significant interaction between age (< 50 years
and ≥ 50 years) and TST when sagittal abdominal diameter was
used as the dependent variable (P = 0.048), and a trend between
these 2 variables when waist circumference served as the dependent variable (P = 0.07). A significant negative association
between TST and both waist circumference and sagittal abdominal diameter was seen in women < 50 years after adjusting for
confounders (Figure 3a and 3b). In addition, TST was associated with sagittal abdominal diameter in women ≥ 50 years (Figure 3a). When analyzing independent associations of different
sleep stages with central obesity in the 2 age groups, both SWS
duration and REM sleep duration were significantly inversely
related with waist circumference in the younger women; REM
sleep duration also showed a relationship with waist circumference in women ≥ 50 years (Figure 3a). REM sleep duration was
further significantly associated with sagittal abdominal diameter in both age groups (Figure 3a and 3b).
DISCUSSION
The main result of this population-based study is the independent inverse relationship between objectively measured
sleep duration, sleep stages, and central obesity in women. The
negative association between sleep duration and measures of
central obesity remained significant also after adjusting for
BMI. In addition, there were independent negative associations
between SWS and central obesity and between REM sleep and
central obesity. These associations were stronger in the younger
(< 50 years) than in the older (≥ 50 years) women.
Several studies have reported a significant inverse relationship between self-reported sleep duration and weight.5-7,10,23,24
Two studies using self-reported sleep duration have failed to
demonstrate any significant independent association with central obesity.25,26 The wider age range in these two studies as
compared with our study may have contributed to the discrepant findings. By using PSG to measure sleep duration (TST),
we found a negative linear association with central obesity after
controlling for confounding variables. Our observations also
indicate that less than 6-7 hours of sleep is associated with a
substantial and gradual increase in waist circumference and abdominal sagittal diameter. In contrast to our results, two previous
studies using objectively measured sleep duration (measured by
wrist activity monitoring or PSG) found no relationship to obesity.12,13 However, the use of BMI as the factor of obesity may
have contributed to these discrepant findings.
In comparison with other measures of central obesity, sagittal abdominal diameter has a stronger correlation with measured metabolic variables, including insulin sensitivity.21 The
association between objectively measured sleep duration and
sagittal abdominal diameter remained significant even after
adjusting for BMI, which indicates that short sleep duration is
more strongly related to central obesity than to general obesity,
irrespective of which of the two methods for assessment of abdominal obesity is used.
Short sleep duration could have an impact on obesity by influencing lifestyle and habits. Lack of sleep may cause daytime
sleepiness and fatigue, which can lead to restriction of physical
activity and, in turn, start a vicious circle of short sleep duration, physical inactivity, and weight gain.27 Moreover, less time
for sleep gives more time for eating.28 Stress and emotional
Figure 3a—Total sleep time and different sleep stages in relation to waist
circumference in women < 50 years and ≥ 50 years.
Figure 3b—Total sleep time and different sleep stages in relation to
sagittal abdominal diameter in women < 50 years and ≥ 50 years.
Results are presented as a decrease in cm of waist circumference per
one-minute increase of different sleep variables. Results are adjusted for
age, physical activity, AHI, smoking and alcohol consumption. TST = Total
sleep time; SWS = Slow wave sleep.
was also true when using the cut off point AHI 5 (P = 0.37 and
0.16, respectively). Therefore, the multivariate analysis model
was performed in the whole group adjusting for AHI as a continuous variable (Table 2). There was an inverse relationship
between TST (hours) and both measures of central obesity after
adjusting for confounders. This adjusted relationship showed
that an increase by 1 hour in TST was associated with a decrease of 1.24 cm in waist circumference and 0.46 cm in abdominal sagittal diameter. SWS (in minutes) was significantly
associated with waist circumference, and there was a trend for
an association between SWS (in minutes) and sagittal abdominal diameter. Duration of REM sleep was associated with both
measures of central obesity. Moreover, the association between
SWS (minutes and percent) and waist circumference remained
significant also after adjustment for BMI. Both TST (hours) and
REM sleep (minutes and percent) was further significantly associated with sagittal abdominal diameter also when adjusting
for BMI (data not shown).
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Sleep Duration and Central Obesity—Theorell-Haglöw et al
disturbance has also been associated with both sleep duration
and obesity and could be a potential link between the two.12
Unfortunately, the present study does not have data on emotional stress.
Loss of both SWS and REM sleep were independently associated with central obesity in the present study, and the associations remained significant after adjusting for BMI, indicating a
stronger relationship with central obesity than general obesity.
Our study also shows that duration of SWS and REM sleep,
rather than the percentage of different sleep stages, is of importance in central obesity. One recent study in elderly men
assessed associations between sleep architecture and body
composition, showing a relationship between SWS and waist
circumference.16 However, no relationship was seen between
REM sleep and body composition. The older age group and different gender may explain the discrepant findings.
Growth hormone, mostly secreted during SWS, is suppressed
by reduced sleep.29 Growth hormone deficiency because of hypopituitarism is associated with visceral obesity, which is reversed by growth hormone replacement therapy.30 In the present
study SWS was independently associated with waist circumference, indicating that the relationship between short sleep duration and central obesity could be mediated through an abnormal
growth hormone secretion pattern. Furthermore, the amount of
REM sleep may have an impact on cortisol levels in that a trend
toward elevated levels of cortisol has been shown with reduced
amounts of REM sleep.31 Because REM sleep was independently associated with both measures of central obesity (waist
circumference and sagittal abdominal diameter), the relationship could be mediated through increased cortisol levels.
Menopausal state has been suggested to have an influence on
sleep and sleep quality.32,33 In addition, menopause is also often
related to weight gain.34 However, in the present female population, the influence of short sleep duration and reduced duration
of SWS or REM sleep on accumulation of abdominal fat was
most pronounced in women < 50 years (when the women were
assumed to be premenopausal). This finding indicates that the
mechanisms underlying the development of abdominal obesity
may start to operate early in life. This observation finds support from the NHANES cohort, in which both men and women
younger but not older than 50 years demonstrated an inverse
univariate relationship between reported short sleep duration
and increased prevalence of overweight or obesity.5 Multivariate analysis of data from a cohort of clinic-based patients
showed no age-related difference in risk of obesity, but there
was a difference between genders, with women sleeping < 8 h
having an increased risk of obesity in contrast to men.35
The present study was conducted in a large population of
women. Nonetheless, there are some limitations to consider
when interpreting the results. Because the response rate in this
study was relatively modest (54%), it could have affected the
results. The non-responders were younger, had lower BMI, and
were more often physically inactive. Still, there was no difference in self-reported sleep duration, smoking, or presence of
somatic disease between responders and non-responders. There
was only one night of polysomnography performed. Polysomnography studies have an inherent risk of a “first-night effect,”
due to disturbance from the polysomnography equipment leading to shorter sleep duration. This may have restricted sleep
SLEEP, Vol. 33, No. 5, 2010
duration in our study, because only 27 of the women slept ≥ 8
h. On the other hand, this might also be a true observation of
sleep, in the sense that sleep duration has decreased over the
past decades,1,2 and PSGs were not performed solely on weekends when people tend to sleep longer. Furthermore, PSG is
the only method available for recording different sleep stages.
In our population-based sample, there was a deliberate oversampling of snorers. Consequently, the prevalence of OSA and
central obesity can be assumed to be higher in this sample than
in the general population.18 However, adjusting for AHI or using sleep efficiency instead of TST as an independent variable
did not significantly change any of the reported results. Furthermore, the study only included women, which may limit the
generalizability of our results.
In conclusion, a relationship was observed between short
sleep duration and central obesity in women, even after controlling for potential confounders. This relationship was most
pronounced in women aged < 50 years. Both loss of SWS and
REM sleep was associated with central obesity and may affect
the relationship between sleep duration and central obesity.
ACKNOWLEDGMENTS
The authors would like to thank Lars Berglund, UCR-Uppsala Clinical Research Center, Uppsala, for his statistical advice.
This study was financially supported by the Swedish Heart
Lung Foundation and by the Uppsala County Association
against Heart and Lung Diseases.
DISCLOSURE STATEMENT
This was not an industry supported study. Dr. Berne has participated in speaking engagements for Astellas, MSD, Novo
Nordisk, Sanofi-Aventis, and Amgen. The other authors have
indicated no financial conflicts of interest.
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