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Sleep duration and central obesity in women – Differences between short sleepers and long sleepers
Sleep Medicine 13 (2012) 1079–1085
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Original Article
Sleep duration and central obesity in women – Differences between short sleepers and long sleepers q,qq Jenny Theorell-Haglöw a,⇑, Lars Berglund b, Christer Janson a, Eva Lindberg a a b
Department of Medical Sciences, Respiratory Medicine and Allergology, Uppsala University, Sweden Department of Medical Sciences, Uppsala Clinical Research Center (UCR), Uppsala University, Sweden
a r t i c l e
i n f o
Article history: Received 20 January 2012 Received in revised form 15 May 2012 Accepted 5 June 2012 Available online 26 July 2012 Keywords: Sleep duration Central obesity Short sleepers Long sleepers Women Population-based
a b s t r a c t Objective: To assess characteristics of short sleepers and long sleepers and to assess association between sleep duration and central obesity in a population-based sample of women. Method: Non-pregnant women P20 years that were randomly selected from the population-registry of Uppsala, Sweden, answered a questionnaire (n = 6461) including questions on sleeping habits and somatic disorders. Results: There was a U-shaped association between sleep duration and waist circumference. Short sleeping women (<5 h) had a waist circumference of 89.2 ± 14.9 cm (mean ± SD) decreasing to 82.9 ± 11.9 cm for women sleeping 7–<8 h and increasing to 89.0 ± 16.7 cm for women sleeping P10 h. Both short sleepers and long sleepers were more often physically inactive, smokers, ill or taking medication, and psychologically distressed than normal sleepers (6–<9 h). In women <50 years both short and long sleep duration were risk factors for central obesity. Short sleep duration remained a risk factor for central obesity, whereas the association with long sleep duration did not reach statistical significance after adjustments. Conclusions: Short sleepers and long sleepers showed differences in characteristics compared to normal sleepers. Furthermore, we showed an independent association between short sleep duration and central obesity, which was strongest in younger women. It is important to identify short sleepers, especially in younger women. Ó 2012 Elsevier B.V. All rights reserved.
1. Introduction Over the past decades sleep duration has decreased [1–3] and, parallel to this, there has been an increase in the prevalence of obesity [4]. Several studies have found relationships between the two conditions [5–11]. Inverse relationships between self-reported sleep duration and obesity as well as U-shaped relationships have been found in both men and women [12,13]. Moreover, short sleep duration is also reported to predict weight gain and obesity later in life [6,8]. In earlier studies the focus has primarily been on sleep duration in relation to general obesity [5–7], whereas the association with central obesity is less clear. Central obesity is a stronger risk factor than body mass index (BMI) for both cardiovascular disease and type 2 diabetes mellitus [4,14,15]. Further, there may
q Work attributed to: Department of Medical Sciences, Respiratory Medicine and Allergology, Uppsala University, Sweden. qq Funding by: The Swedish Heart Lung Foundation, The Swedish Heart Lung Association and the Uppsala County Association against Heart and Lung Diseases. ⇑ Corresponding author. Address: Department of Medical Sciences, Respiratory Medicine and Allergology, Uppsala University, Box 256, 751 05 Uppsala, Sweden. Tel.: +46 18 611 02 42; fax: +46 18 611 02 28. E-mail address: [email protected] (J. Theorell-Haglöw).
1389-9457/$ - see front matter Ó 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.sleep.2012.06.013
be differences in factors related to central obesity in short sleepers versus long sleepers [16–18]. In a previous study in women we found an inverse relationship between objectively measured sleep duration and central obesity [19]. This study included 400 women from a population-based sample. Therefore, we wanted to investigate the relationship between sleep duration and central obesity in a larger population and also assess if there are different factors associated with central obesity in short sleepers compared to long sleepers. We hypothesized that both short and long sleep duration was related to central obesity and that there may be differences between the groups in factors related to central obesity. We further hypothesized that there may be differences between younger and older women. Consequently, the aim of this study was to analyze associations between self-reported sleep duration and central obesity and also to assess different factors in relation to central obesity in short and long sleepers in a population-based sample of women.
2. Methods In this population-based study (‘‘Sleep and Health in women’’) [20], a questionnaire on sleeping habits and somatic disorders
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was sent to women aged P20 years, randomly selected from the population registry of the city of Uppsala, Sweden The response rate was 71.6% (n = 7051). The final study population included the 6461 non-pregnant women who had reported their sleep duration and waist circumference. The questionnaire consisted of 109 questions and has previously been described in detail [20]. Briefly, the questionnaire comprised questions on sleep duration, snoring habits, insomnia, occupational status, shift work, civil status, physical activity, smoking, alcohol dependence, and anxiety and depression. To assess sleep duration (h/night) the women were asked ‘‘How many hours do you on average sleep during the night?’’ Sleep duration was grouped by hours slept but was also classified into three categories: short sleepers (<6 h/night), normal sleepers (6–<9 h/night), and long sleepers (P9 h/night). In conjunction with the questionnaire, the women were given a tape measure and instructions on how to measure their waist circumference [20]. A waist circumference P88 cm was used to define central obesity according to NCEP (National Cholesterol Education Program) criteria [21]. BMI was calculated from self-reported height and weight. Six questions assessed smoking habits. Based on the participants’ responses they were categorized as ‘‘current smokers,’’ ‘‘ex-smokers’’ (i.e., had quit smoking at least six months before answering the questionnaire), or ‘‘non-smokers’’ (i.e., never smoked). Alcohol dependence was assessed by the CAGE (acronym for cut down, annoyed by criticism, guilty about drinking, and eye-opener drinks) alcohol and screening questionnaire [22]. Psychological distress was assessed using the Hospital Anxiety and Depression (HAD) scale [23]. The participants’ physical activity was analyzed by four questions adopted from a questionnaire used in a large population-based study on the correlation of physical activity and mortality [24]. Occupational status was categorized into the following categories: working full-time (P30 h/week), working part time (<30 h/ week)/working at home, student, unemployed, sick leave/early retirement. The participants were also asked to ascertain how many months they had been working nights or shifts over the past 10 years. A cut-off point of 60 months was chosen when analyzing working nights or shifts as risk factors for EDS and fatigue. Civil status was classified into two categories: married/living together and single (including divorced and widowed women). The women were asked if they had any somatic disease(s) that required regular medical attention. Somatic diseases were: asthma/chronic obstructive pulmonary disease (COPD), cardiovascular disease, diabetes, gastric ulcer/reflux, back/joint problems, fibromyalgia, gynecological problems and neurological problems. In addition, the women were asked if they were taking any medication on a regular basis. Medication was indicated if taking any of the following: beta blockers, beta 2 agonists, diabetes medication, or benzodiazepines/sleep medicine as these were considered to potentially affect sleep or obesity.
3. Statistical analyses Statistical analyses were performed using Stata 10 (Stata Corporation, College Station, TX, USA). Univariate analyses were conducted using the unpaired t-test for continuous variables and the chi-squared test for categorical variables to compare the sleep duration groups. All significant variables from the univariate analyses were then entered into a multiple model, which was performed using logistic regression with central obesity as a dependent variable. The results from the logistic regression are presented as adjusted odds ratios (ORs) with 95% confidence intervals (95% CI).
Associations between sleep duration and central obesity (waist circumference) were analyzed using a multiple regression analysis. Results from the regression analysis are presented as adjusted b-values with p-values. To analyze the presence of a U-shaped relationship between sleep duration and central obesity the squared sleep duration was entered into the multiple regression analysis. A two-sided p-value < 0.05 was considered a statistically significant result. In a previous study we have seen that short sleep duration has most importance in younger women (age < 50 years) [19] and, in addition, there was a significant interaction between age and sleep duration (p = 0.014) for central obesity. Therefore, the population was divided by age above and below 50 years in some analyses. The study was approved by the Ethics Committee of the Medical Faculty at Uppsala University and all participants gave their informed consent before participating.
4. Results Compared with normal sleepers (6–<9 h), both short sleepers and long sleepers were more centrally obese and had greater neck and waist circumference and short sleepers were even more centrally obese than long sleepers. Both short and long sleepers were more physically inactive, more likely to be smokers, had an illness, or were taking medication, and more often suffered from psychological distress compared with normal sleepers. In addition, both short sleepers and long sleepers were more often married or living with someone and were more often sick leaved or retired early. In contrast, compared with normal sleepers, short sleepers were older and had higher BMI, whereas there were no differences for the long sleepers. Long sleepers, on the other hand, were more often students or seeking employment compared with normal sleepers short sleepers. When further comparing short sleepers with long sleepers, the short sleepers were more seldom alcohol dependent and were more often suffering from physical illness and also from psychological distress. There were also differences in occupational status as short sleepers were more often working full-time and also part-time, but also more often on sick-leave or early retirement than long sleepers (Table 1). In younger women (age < 50 years), both short sleepers and long sleepers shared many of the same characteristics as in the whole group. However, increased neck circumference (33.1 ± 3.6 versus 32.7 ± 2.5 cm; p = 0.011) and waist circumference (84.1 ± 14.7 versus 80.3 ± 10.9 cm; p < 0.0001) were seen only in short sleepers in the younger age group. Short sleepers were also older (36.6 ± 8.5 versus 33.4 ± 8.9 years; p < 0.0001). As in the whole population, long sleepers in the younger age group were more seldom working full-time (19.0% versus 42.8%; p < 0.0001) and were more often students (41.7% versus 25.5%; p < 0.0001) or seeking employment (7.4% versus 2.4%; p < 0.0001) compared with normal sleepers (6–<9 h). Furthermore, long sleepers were also younger (29.4 ± 8.6 versus 33.4 ± 8.9; p < 0.0001) and more often living with someone (41.9% versus 33.0%; p = 0.011) compared with normal sleepers. In comparison with long sleepers, short sleepers in the younger age group were older (36.6 ± 8.5 versus 29.4 ± 8.9 years; p < 0.0001), had greater waist circumference (84.1 ± 14.7 versus 81.0 ± 13.0 cm; p = 0.016), higher BMI (24.5 ± 5.0 versus 23.5 ± 4.3 cm; p = 0.024), and were more likely to be smokers (28.2% versus 22.7%; p = 0.026). In addition, the short sleepers were more often suffering from physical illness (25.6% versus 18.0%; p = 0.036), anxiety, and depression (31.4% versus 14.5%; p < 0.0001) and were more often working full-time (43.5% versus 19.0%; p < 0.0001), on sick-leave or early retired (10.4% versus 7.8%; p < 0.0001), and there were also more shift workers among the short sleepers (8.3% versus 3.2%; p = 0.042).
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J. Theorell-Haglöw et al. / Sleep Medicine 13 (2012) 1079–1085 Table 1 Characteristics of the study population. Normal sleepers 6–<9 h (n = 5661)*
Short sleepers <6 h (n = 859)*
Sleep duration (h) Central obesity (P88 cm) Neck circumference Waist circumference BMI (kg/m2)
6.9 ± 1.2 33.3 33.5 ± 2.9 84.0 ± 12.8 24.1 ± 4.1
N/A 31.3 33.4 ± 2.8 83.4 ± 12.2 24.0 ± 4.0
N/A 43.2 34.1 ± 33.9 87.4 ± 15.0 24.9 ± 4.6
BMI (group) <20 20-<25 25–<30 P30
11.1 55.3 24.1 9.4
11.2 57.0 23.4 8.4
9.8 48.2 28.3 13.7
Snoring
7.7
7.4
8.4
p Value
<0.0001 <0.0001 <0.0001 <0.0001
Long sleepers P9 h (n = 351)* N/A 38.5 34.0 ± 3.3 85.3 ± 14.1 24.3 ± 4.5
<0.0001
Physical activity High Medium Low
19.4 61.7 18.9
20.7 62.0 17.3
12.7 61.2 26.2
Smoking Non smoker Ex-smoker Current smoker Alcohol dependency Physical illness Medication
60.5 22.4 17.1 6.0 22.1 12.0
61.3 22.4 16.3 5.8 19.2 9.8
55.9 24.3 19.8 5.7 37.8 21.7
Psychological distress None Anxiety Depression Anxiety and depression
63.6 22.2 3.4 10.8
66.6 21.6 3.2 8.7
46.8 26.1 4.3 22.8
0.32
9.8
<0.0001
0.96 <0.0001 <0.0001
57.0 20.1 22.9 9.6 29.3 17.4
<0.0001
34.6
33.1
40.9
46.1 18.1 18.9 2.6 5.0
47.5 18.6 19.2 2.4 3.5
47.5 16.7 10.8 2.5 12.3
Working shifts
4.2
4.4
4.8
Short versus Long sleepers p Value
0.007 0.0002 0.005 0.21
N/A 0.15 0.62 0.035 0.024
0.002
0.067
0.10
0.44
0.001
0.22
0.006
0.21
0.004 <0.0001 <0.0001
0.020 0.005 0.094
0.003
<0.0001
0.001 <0.0001
0.86 <0.0001
0.15
0.002
16.5 58.6 24.9 0.007
Married/living together Occupation Full-time Part-time/working at home Student Seeking employment Sick-leave/early retirement
p Value
14.8 48.2 24.8 12.3
59.7 21.5 4.9 13.9 <0.0001 <0.0001
41.5 21.1 13.9 32.1 7.1 11.8
<0.0001
2.3
All values are indicated as % or mean ± SD.
In women above 50 years, both short sleepers and long sleepers shared some of the same characteristics as in the whole population, but, in addition, they were older (65.1 ± 10.7 versus 62.6 ± 10.2 years; p = 0.006) and were more seldom working full-time (28.1% versus 60.7%; p < 0.0001) compared with normal sleepers (6–<9 h). A low level of physical activity compared with normal sleepers (28.6% versus 20.5%; p < 0.0001) was seen only in short sleepers in women above 50 years and short sleepers were also more seldom snorers (8.1% versus 11.9%; p = 0.018) and more seldom shift workers (1.96% versus 2.01%; p = 0.011). Long sleepers had greater neck (35.4 ± 2.8 verses 34.5 ± 2.8 cm; p = 0.0005) and waist (91.9 ± 13.1 versus 88.4 ± 12.5 cm; p = 0.002) circumference and were more often alcohol dependent (6.5% versus 2.3%; p = 0.004) compared with normal sleepers. Long sleepers in comparison with short sleepers in the older age group had narrower neck circumference (34.8 ± 3.0 verses 35.4 ± 2.8 cm; p = 0.030) and were more seldom snorers (8.1% versus 14.5%; p = 0.030). In addition, short sleepers were more seldom smokers (14.1% versus 23.3%; p = 0.013) and alcohol dependent (2.6% versus 6.5%; p = 0.037) compared with long sleepers. However, short sleepers were more often suffering from anxiety (23.9% versus 11.9%; p = 0.022) or both anxiety and depression (16.8% versus 12.7%; p = 0.022) when compared with long sleepers. Furthermore, short sleepers in the older age group were more often working full-time (53.0% versus 28.1%; p = 0.007) and were more seldom on sick-leave or early retired (15.0% versus 25.0%; p = 0.007) compared to long sleepers.
5. Associations with central obesity Using the squared sleep duration there was a U-shaped relationship between reported sleep duration and waist circumference (p < 0.0001 for comparison with a linear relationship; Fig. 1). Also this relationship remained when adjusting for confounders (p = 0.003 for comparison with a linear relationship; Table 2). A mean difference of six centimeters in waist circumference was seen between women sleeping <5 h and those sleeping 7–<8 h. In addition, there was also
92 Waist circumference (cm)
*
All women (n = 6871)*
90 88 86 84 82 80 <5h n=253
5-<6h n=606
6-<7h n=1,703
7-<8h n=2,484
8-<9h n=1,474
9-<10h n=276
>=10h n=75
Sl Sleep d duration ti (h (hours)) Fig. 1. Waist circumference in relation to sleep duration. Results are presented as mean ± SE.
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Table 2 Associations between sleep duration and waist circumference. Waist circumference All (n = 5773)
*
<50 years (n = 3625)
P50 years (n = 2148)
Adj. b (95% CI)*
p Value
Adj. b (95% CI)*
p Value
Adj. b (95% CI)*
p Value
Sleep duration (h) Squared sleep duration (h2) Age (years) Snoring
2.81 ( 4.58 to 1.04) 0.19 (0.064–0.32) 0.22 (0.20–0.24) 6.85 (5.71–7.99)
0.002 0.003 <0.0001 <0.0001
3.22 ( 5.77 to 0.68) 0.21 (0.33–0.40) 0.25 (0.21–0.29) 7.17 (5.54–8.81)
0.013 0.020 <0.0001 <0.0001
2.96 ( 5.54 to 0.38) 0.21 (0.025–0.40) 0.18 (0.12–0.24) 6.38 (4.73–8.03)
0.025 0.027 <0.0001 <0.0001
Physical activity High Medium Low
Reference 3.10 (2.32–3.87) 5.84 (4.82–6.85)
<0.0001 <0.0001
2.83 (2.00–3.67) 5.60 (4.44–6.76)
<0.0001 <0.0001
3.61 (1.71–5.50) 6.49 (4.29–8.69)
<0.0001 <0.0001
Smoking Non smoker Ex-smoker Current smoker
Reference 1.009 (027–1.74) 0.23 ( 1.06 to 0.59)
0.007 0.58
1.17 (0.22–2.13) 0.28 ( 0.71 to 1.28)
0.016 0.58
0.42 ( 0.79 to 1.63) 1.60 ( 3.10 to 0.90)
0.50 0.038
Alcohol dependency
0.38 ( 0.88 to 1.64)
0.55
0.40 ( 0.92 to 1.71)
0.56
0.56 ( 2.78 to 3.91)
0.74
Psychological distress None Anxiety Depression Anxiety and depression
Reference 1.55 ( 2.92 to 0.82) 0.61 ( 1.09 to 2.32) 0.34 ( 0.69 to 1.36)
1.05 ( 1.88 to 0.22) 3.00 (0.67–5.35) 0.21 ( 1.00 to 1.42)
0.013 0.012 0.73
2.50 ( 3.98 to 1.02) 1.69 ( 4.25 to 0.87) 0.60 ( 1.28 to 2.47)
0.001 0.20 0.53
Working shifts
1.30 ( 0.28 to 2.80)
2.05 (0.46–3.64)
0.011
2.45 ( 6.21 to 1.31)
0.20
<0.0001 0.48 0.52 0.09
Adjusted for all the variables in the table.
a difference of six centimeters between the group sleeping P10 h and women sleeping 7–<8 h (Fig. 1). In addition, habitual snoring,
medium or low levels of activity and anxiety were all independently associated with waist circumference (Table 2).
Table 3 Multiple analyses for women below and above age 50 years. Central obesity (waist circumference P88 cm) Age <50 years (n = 3625)
*
Age P50 years (n = 2148)
Unadj. OR (95% CI)
p Value
Adj. OR (95% CI)*
Short sleep duration (<6 h) Normal sleep duration (6–<9 h) Long sleep duration (P9 h) Age (years) Snoring
1.83 1.0 1.39 1.06 3.82
(1.43–2.34)
<0.0001
(1.01–1.91) (1.05–1.07) (2.86–5.10)
0.044 <0.0001 <0.0001
1.36 1.0 1.20 1.04 3.11
Physical activity High Medium Low
1.0 2.41 (1.95–2.97) 4.04 (3.15–5.17)
Smoking Non smoker Ex-smoker Current smoker
p Value
Unadj. OR (95% CI)
(1.02–1.82)
0.036
(0.82–1.76) (1.03–1.06) (2.25–4.31)
0.34 <0.0001 <0.0001
1.05 1.0 1.36 1.03 2.05
<0.0001 <0.0001
1.0 1.87 (1.49–2.35) 3.28 (2.49–4.33)
1.0 1.58 (1.30–1.90) 1.61 (1.33–1.96)
<0.0001 <0.0001
Alcohol dependency Physical illness Medication
0.97 (0.74–1.28) 1.89 (1.54–2.31) 1.64 (1.21–2.22)
Psychological distress None Anxiety Depression Anxiety and Depression
p Value
Adj. OR (95% CI)*
p Value
(0.64–1.25)
0.51
(0.96–3.41) (1.03–1.09) (1.57–3.09)
0.064 <0.0001 <0.0001
(0.86–1.29)
0.63
(0.95–1.94) (1.02–1.04) (1.59–2.65)
0.095 <0.0001 <0.0001
0.89 1.0 1.81 1.06 2.19
<0.0001 <0.0001
1.0 1.89 (1.40–2.54) 3.41 (2.45–4.75)
<0.0001 <0.0001
1.0 1.56 (1.05–2.33) 2.01 (1.25–3.23)
0.028 0.004
1.0 1.26 (1.02–1.56) 1.15 (0.92–1.44)
0.030 0.23
1.0 1.00 (0.84–1.19) 0.91 (0.73–1.13)
0.98 0.38
1.0 1.31 (1.0008–1.71) 1.13 (0.83–1.55)
0.049 0.44
0.85 <0.0001 0.001
1.02 (0.74–1.40) 1.34 (1.04–1.76) 0.93 (0.63–1.38)
0.89 0.027 0.73
1.21 (0.73–1.99) 1.72 (1.47–2.02) 1.75 (1.45–2.11)
0.46 <0.0001 <0.0001
1.15 (0.61–2.15) 1.43 (1.07–1.92) 1.52 (1.46–2.22)
0.67 0.017 0.028
1.0 0.74 (0.62–0.90) 2.02 (1.30–3.13) 1.30 (1.03–1.64)
0.002 0.002 0.028
1.0 0.73 (0.59–0.90) 1.21 (0.74–1.99) 0.95 (0.73–1.25)
0.003 0.45 0.72
1.0 0.68 (0.54–0.85) 1.07 (0.74–1.57) 1.07 (0.82–1.41)
0.001 0.72 0.62
1.0 0.47 (0.34–0.67) 1.01 (0.54–1.88) 0.72 (0.47–1.10)
<0.0001 0.97 0.12
Married/living together
0.78 (0.66–0.92)
0.003
1.09 (0.90–1.32)
0.38
1.29 (1.10–1.51)
0.002
1.15 (0.86–1.52)
0.34
Occupation Full-time Part-time/working at home Student Seeking employment Sick-leave/early retirement
1.0 1.29 0.52 1.95 3.32
1.0 1.26 0.92 2.25 2.07
0.035 0.56 0.001 0.002
1.0 1.39 1.73 1.73 2.47
1.0 1.35 2.22 1.89 1.96
0.081 0.15 0.089 0.002
Working shifts
1.40 (1.02–1.93)
0.36
0.65 (0.35–1.18)
(1.06–1.57) (0.42–0.65) (1.28–2.98) (2.25–4.90)
Adjusted for all the variables in the table.
0.011 <0.0001 0.002 <0.0001 0.038
(1.02–1.57) (0.71–1.20) (1.37–3.69) (1.29–3.32)
1.18 (0.83–1.67)
(1.03–1.86) (0.68–4.40) (0.90–3.32) (1.74–3.51)
0.030 0.25 0.10 <0.0001 0.16
(0.96–1.89) (0.75–6.57) (0.91–3.95) (1.29–2.99)
0.72 (0.35–1.48)
0.37
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Fig. 2. Associations between short sleep duration (sleep time <6 h) and central obesity (waist circumference >88 cm) by age groups. Results are presented as adjusted OR’s with 95% CI after adjusting for physical activity, alcohol dependency, psychological distress, physical illness, taking medication, marital status, occupation, and working shifts.
In the unadjusted analysis in women <50 years both short and long sleep duration were shown as risk factors for central obesity. In addition, age, physical inactivity, smoking status, physical illness, medication, psychological distress, and several socioeconomic factors were associated with central obesity. Having anxiety alone showed a reduced risk of central obesity. When adjusting the model for confounders, short sleep duration remained a risk factor for central obesity, whereas long sleep duration did not reach statistical significance. In addition, age, physical inactivity, ex-smoking, and physical illness was all still associated with central obesity. Furthermore, occupational factors remained significantly associated with central obesity. Anxiety still reduced the risk of central obesity (Table 3). In women above 50 years, neither short nor long sleep duration were risk factors for central obesity, although there was a trend for an association with long sleep duration. However, age, physical inactivity, physical illness, medication, and socioeconomic factors were shown to be associated with central obesity. Having anxiety alone also showed a reduced risk of central obesity also in this age group. In the adjusted model for women above 50 years of age, physical inactivity, physical illness, being on medication, being on sick-leave, or being early retired were all still associated with central obesity. Also, in this age group having anxiety showed a reduced risk of central obesity (Table 3). When further subdividing the younger women into age groups of 10 year intervals we found that the association between short sleep duration and central obesity decreased with increasing age. This decrease also remained when adjusting for confounders (Fig. 2).
6. Discussion This study showed that there were differences between short sleepers and long sleepers compared to normal sleepers. In addition, we showed a U-shaped association between sleep duration and central obesity. When adjusting for confounders, only the relationship between short sleep and central obesity remained. Further-
more, the association between short sleep duration and central obesity was strongest in younger women. In unadjusted analyses both short and long sleep duration were associated with central obesity in younger women. Short sleep duration further remained associated with central obesity after adjusting for potential confounders in the younger women. However, there was no relationship between sleep duration and central obesity in the women P50 years. Several studies have analyzed the relation between self-reported sleep duration and obesity by measuring BMI [7–10,25,26], weight [5], or weight gain over time [5,6,27]. Both short [26,28–30] and long sleep duration have been associated with higher risk of obesity [25], and the optimal sleep duration has been suggested to be 7 h per night in both males and females, as this is the sleep duration where optimal BMI is seen [31]. A U-shaped association between self-reported sleep duration and BMI was shown in a large sample of middle-aged men and women independent of age and sex [9]. Two studies showing a U-shaped association in unadjusted data did, however, not show the curve linear relationship when adjusting for confounders, although the relationship between short sleep duration and BMI was still significant after controlling for confounders [6,10]. This is consistent with the results from the present study where a relationship with central obesity was seen for short sleep duration. Some previous studies have performed age-divided analyses. In a longitudinal epidemiological study, Hairston et al. showed that self-reported short as well as long sleep duration increased BMI, subcutaneous adipose tissue, and visceral adipose tissue measured by CT scan in persons younger but not older than 40 years [32]. From the NHANES cohort, both men and women below but not above age 50 years showed an inverse relationship between short reported sleep duration and increased prevalence of overweight or obesity in univariate analyses [6]. Apart from sleep duration several factors were associated with central obesity in the current study. In both women below and above 50 years of age, medium or low levels of physical activity, physical illness, or being on sick-leave or early retired were shown to be associated with central obesity. Having anxiety alone showed
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a reduced risk of central obesity. The association between low socioeconomic status and health has been suggested to be mediated by short sleep, and it has been shown that state of sleep debt is associated with decreased glucose tolerance, increased evening cortisol, and increased sympathetic activity [37]. Further, the relationship between long work hours and obesity has also been shown to be mediated by short sleep duration [38]. The present study further showed that, although short sleepers and long sleepers shared many of the same characteristics, there were also differences between them as short sleepers were older and had higher BMI, whereas long sleepers were more often students or seeking employment. Also, when dividing the women into age groups (over and under 50 years), there were differences between short sleepers and long sleepers. In the younger women short sleepers compared with normal sleepers were older and had greater neck and waist circumference as well as BMI and they more often suffered from psychological distress. As in the whole population, long sleepers were more often students or unemployed. In women above the age of 50 years, short sleepers were more seldom snorers, were more often physically inactive, and were more seldom shift workers compared with normal sleepers. The long sleepers in women P50 years had greater neck and waist circumference compared with normal sleepers. Few earlier studies on factors relating to short and long sleep duration have been performed in an adult population-based sample. However, in a community-based study, Park and co-workers [18] showed that both short and long sleep duration (<5 and P9 h, respectively) was correlated with unemployment, physical illness, anxiety, and also alcohol dependency. Short sleep duration was further associated with being single and being obese, whereas long sleep duration was associated with younger age and also underweight [18], a result in discrepancy with the results from the present study. Unfortunately, there were no age divided analyses performed [18]. From the Nurses Health Study use of antidepressants or benzodiazepines as well as some physical illnesses were strongly correlated with prolonged sleep [16]. Short sleep duration and sleep disturbances have been linked to several physical illnesses such as diabetes [33], hypertension [34] and the metabolic syndrome [35]. In addition, short sleep duration has also been associated with mortality risk in women [36]. In the present study both short and long sleep duration were associated with physical illness; however, in women P50 years, there was only a significant association between short sleep duration and physical illness. This study was conducted in a large population of women and had a high response rate. Nonetheless, there are some limitations to consider when interpreting the results. All the data are selfreported. However, for 400 of the women waist circumference was measured objectively two years later. In spite of the time lapse between the two measures there was good correlation between the two measures (b = 0.85; p < 0.0001). Also, as the study is cross-sectional, causality is difficult to infer. Furthermore, the fact that the study only included women may limit the generalizability of our results. In conclusion, there are differences between short sleepers and long sleepers compared to normal sleepers. Furthermore, we show an association between short sleep duration and central obesity when adjusting for confounders. This association was strongest in younger women and, therefore, it is important to identify short sleepers, especially in younger women.
Conflict of interest The ICMJE Uniform Disclosure Form for Potential Conflicts of Interest associated with this article can be viewed by clicking
on the following link: http://dx.doi.org/10.1016/j.sleep.2012. 06.013.
Acknowledgements This study was financially supported by the Swedish Heart Lung Foundation and by the Swedish Heart Lung Foundation and the Uppsala County Association against Heart and Lung Diseases. References [1] Hammond EC. Some Preliminary Findings on Physical Complaints from a Prospective Study of 1,064,004 Men and Women. Am J Public Health Nations Health 1964;54:11–23. [2] Kripke DF, Simons RN, Garfinkel L, Hammond EC. Short and long sleep and sleeping pills. Is increased mortality associated? Arch Gen Psychiatry 1979;36:103–16. [3] Walsleben JA, Kapur VK, Newman AB, Shahar E, Bootzin RR, Rosemberg CE, et al. Sleep and reported daytime sleepiness in normal subjects: the Sleep Heart Health Study. Sleep 2004;27:293–8. [4] Obesity: preventing and managing the global epidemic. Report of a WHO consultation. Technical report; 2000. [5] Patel SR, Malhotra A, White DP, Gottlieb DJ, Hu FB. Association between reduced sleep and weight gain in women. Am J Epidemiol 2006;164:947–54. [6] Gangwisch JE, Malaspina D, Boden-Albala B, Heymsfield SB. Inadequate sleep as a risk factor for obesity: analyses of the NHANES I. Sleep 2005;28:1289–96. [7] Vorona RD, Winn MP, Babineau TW, Eng BP, Feldman HR, Ware JC. Overweight and obese patients in a primary care population report less sleep than patients with a normal body mass index. Arch Intern Med 2005;165:25–30. [8] Hasler G, Buysse DJ, Klaghofer R, Gamma A, Ajdacic V, Eich D, et al. The association between short sleep duration and obesity in young adults: a 13year prospective study. Sleep 2004;27:661–6. [9] Taheri S, Lin L, Austin D, Young T, Mignot E. Short sleep duration is associated with reduced leptin, elevated ghrelin, and increased body mass index. PLoS Med 2004;1:e62. [10] Singh M, Drake CL, Roehrs T, Hudgel DW, Roth T. The association between obesity and short sleep duration: a population-based study. J Clin Sleep Med 2005;1:357–63. [11] Vgontzas AN, Lin HM, Papaliaga M, Calhoun S, Vela-Bueno A, Chrousos GP, et al. Short sleep duration and obesity: the role of emotional stress and sleep disturbances. Int J Obes (Lond) 2008;32:801–9. [12] Buscemi D, Kumar A, Nugent R, Nugent K. Short sleep times predict obesity in internal medicine clinic patients. J Clin Sleep Med 2007;3:681–8. [13] Kripke DF, Garfinkel L, Wingard DL, Klauber MR, Marler MR. Mortality associated with sleep duration and insomnia. Arch Gen Psychiatry 2002;59:131–6. [14] Dalton M, Cameron AJ, Zimmet PZ, Shaw JE, Jolley D, Dunstan DW, et al. Waist circumference, waist-hip ratio and body mass index and their correlation with cardiovascular disease risk factors in Australian adults. J Intern Med 2003;254:555–63. [15] Janssen I, Katzmarzyk PT, Ross R. Waist circumference and not body mass index explains obesity-related health risk. Am J Clin Nutr 2004;79:379–84. [16] Patel SR, Malhotra A, Gottlieb DJ, White DP, Hu FB. Correlates of long sleep duration. Sleep 2006;29:881–9. [17] Magee CA, Iverson DC, Caputi P. Factors associated with short and long sleep. Prev Med 2009;49:461–7. [18] Park S, Cho MJ, Chang SM, Bae JN, Jeon HJ, Cho SJ, et al. Relationships of sleep duration with sociodemographic and health-related factors, psychiatric disorders and sleep disturbances in a community sample of Korean adults. J Sleep Res 2010;19:567–77. [19] Theorell-Haglow J, Berne C, Janson C, Sahlin C, Lindberg E. Associations between short sleep duration and central obesity in women. Sleep 2010;33:593–8. [20] Theorell-Haglöw J, Lindberg E, Janson C. What are the Important Risk Factors for Daytime Sleepiness and Fatigue in Women? Sleep 2006;29:751–7. [21] Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III). JAMA 2001;285:2486– 97. [22] Beresford TP, Blow FC, Hill E, Singer K, Lucey MR. Comparison of CAGE questionnaire and computer-assited laboratory profiles in screening for covert alcoholism. Lancet 1990;336:482–5. [23] Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand 1983;67:361–70. [24] Lissner L, Bengtsson C, Björkelund C, Wedel H. Physical activity levels and changes in relation to longevity. A prospective study of Swedish women. Am J Epidemiol 1996;143:54–62. [25] Buxton OM, Marcelli E. Short and long sleep are positively associated with obesity, diabetes, hypertension, and cardiovascular disease among adults in the United States. Soc Sci Med 2010;71:1027–36.
J. Theorell-Haglöw et al. / Sleep Medicine 13 (2012) 1079–1085 [26] Stranges S, Cappuccio FP, Kandala NB, Miller MA, Taggart FM, Kumari M, et al. Cross-sectional versus prospective associations of sleep duration with changes in relative weight and body fat distribution: the Whitehall II Study. Am J Epidemiol 2008;167:321–9. [27] Chaput JP, Despres JP, Bouchard C, Tremblay A. The association between sleep duration and weight gain in adults: a 6-year prospective study from the Quebec Family Study. Sleep 2008;31:517–23. [28] Magee CA, Iverson DC, Caputi P. Sleep Duration and Obesity in Middle-aged Australian Adults. Obesity (Silver Spring) 2010;18:420–1. [29] Chaput JP, Despres JP, Bouchard C, Tremblay A. Short sleep duration is associated with reduced leptin levels and increased adiposity: Results from the Quebec family study. Obesity (Silver Spring) 2007;15:253–61. [30] Patel SR, Blackwell T, Redline S, Ancoli-Israel S, Cauley JA, Hillier TA, et al. The association between sleep duration and obesity in older adults. Int J Obes (Lond) 2008;32:1825–34. [31] Adamkova V, Hubacek JA, Lanska V, Vrablik M, Kralova Lesna I, Suchanek P, et al. Association between duration of the sleep and body weight. Physiol Res 2009;58 Suppl 1:S27–31. [32] Hairston KG, Bryer-Ash M, Norris JM, Haffner S, Bowden DW, Wagenknecht LE. Sleep duration and five-year abdominal fat accumulation in a minority cohort: the IRAS family study. Sleep 2010;33:289–95.
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[33] Van Cauter E, Spiegel K. Sleep as a mediator of the relationship between socioeconomic status and health: a hypothesis. Ann N Y Acad Sci 1999;896:254–61. [34] Magee CA, Caputi P, Iverson DC. Short sleep mediates the association between long work hours and increased body mass index. J Behav Med 2011;34:83–91. [35] Bjorkelund C, Bondyr-Carlsson D, Lapidus L, Lissner L, Mansson J, Skoog I, et al. Sleep disturbances in midlife unrelated to 32-year diabetes incidence: the prospective population study of women in Gothenburg. Diabetes Care 2005;28:2739–44. [36] Gangwisch JE, Heymsfield SB, Boden-Albala B, Buijs RM, Kreier F, Pickering TG, et al. Short sleep duration as a risk factor for hypertension: analyses of the first National Health and Nutrition Examination Survey. Hypertension 2006;47:833–9. [37] Hall MH, Muldoon MF, Jennings JR, Buysse DJ, Flory JD, Manuck SB. Selfreported sleep duration is associated with the metabolic syndrome in midlife adults. Sleep 2008;31:635–43. [38] Patel SR, Ayas NT, Malhotra MR, et al. A prospective study of sleep duration and mortality risk in women. Sleep 2004;27:440–4.
Contents lists available at SciVerse ScienceDirect
Sleep Medicine journal homepage: www.elsevier.com/locate/sleep
Original Article
Sleep duration and central obesity in women – Differences between short sleepers and long sleepers q,qq Jenny Theorell-Haglöw a,⇑, Lars Berglund b, Christer Janson a, Eva Lindberg a a b
Department of Medical Sciences, Respiratory Medicine and Allergology, Uppsala University, Sweden Department of Medical Sciences, Uppsala Clinical Research Center (UCR), Uppsala University, Sweden
a r t i c l e
i n f o
Article history: Received 20 January 2012 Received in revised form 15 May 2012 Accepted 5 June 2012 Available online 26 July 2012 Keywords: Sleep duration Central obesity Short sleepers Long sleepers Women Population-based
a b s t r a c t Objective: To assess characteristics of short sleepers and long sleepers and to assess association between sleep duration and central obesity in a population-based sample of women. Method: Non-pregnant women P20 years that were randomly selected from the population-registry of Uppsala, Sweden, answered a questionnaire (n = 6461) including questions on sleeping habits and somatic disorders. Results: There was a U-shaped association between sleep duration and waist circumference. Short sleeping women (<5 h) had a waist circumference of 89.2 ± 14.9 cm (mean ± SD) decreasing to 82.9 ± 11.9 cm for women sleeping 7–<8 h and increasing to 89.0 ± 16.7 cm for women sleeping P10 h. Both short sleepers and long sleepers were more often physically inactive, smokers, ill or taking medication, and psychologically distressed than normal sleepers (6–<9 h). In women <50 years both short and long sleep duration were risk factors for central obesity. Short sleep duration remained a risk factor for central obesity, whereas the association with long sleep duration did not reach statistical significance after adjustments. Conclusions: Short sleepers and long sleepers showed differences in characteristics compared to normal sleepers. Furthermore, we showed an independent association between short sleep duration and central obesity, which was strongest in younger women. It is important to identify short sleepers, especially in younger women. Ó 2012 Elsevier B.V. All rights reserved.
1. Introduction Over the past decades sleep duration has decreased [1–3] and, parallel to this, there has been an increase in the prevalence of obesity [4]. Several studies have found relationships between the two conditions [5–11]. Inverse relationships between self-reported sleep duration and obesity as well as U-shaped relationships have been found in both men and women [12,13]. Moreover, short sleep duration is also reported to predict weight gain and obesity later in life [6,8]. In earlier studies the focus has primarily been on sleep duration in relation to general obesity [5–7], whereas the association with central obesity is less clear. Central obesity is a stronger risk factor than body mass index (BMI) for both cardiovascular disease and type 2 diabetes mellitus [4,14,15]. Further, there may
q Work attributed to: Department of Medical Sciences, Respiratory Medicine and Allergology, Uppsala University, Sweden. qq Funding by: The Swedish Heart Lung Foundation, The Swedish Heart Lung Association and the Uppsala County Association against Heart and Lung Diseases. ⇑ Corresponding author. Address: Department of Medical Sciences, Respiratory Medicine and Allergology, Uppsala University, Box 256, 751 05 Uppsala, Sweden. Tel.: +46 18 611 02 42; fax: +46 18 611 02 28. E-mail address: [email protected] (J. Theorell-Haglöw).
1389-9457/$ - see front matter Ó 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.sleep.2012.06.013
be differences in factors related to central obesity in short sleepers versus long sleepers [16–18]. In a previous study in women we found an inverse relationship between objectively measured sleep duration and central obesity [19]. This study included 400 women from a population-based sample. Therefore, we wanted to investigate the relationship between sleep duration and central obesity in a larger population and also assess if there are different factors associated with central obesity in short sleepers compared to long sleepers. We hypothesized that both short and long sleep duration was related to central obesity and that there may be differences between the groups in factors related to central obesity. We further hypothesized that there may be differences between younger and older women. Consequently, the aim of this study was to analyze associations between self-reported sleep duration and central obesity and also to assess different factors in relation to central obesity in short and long sleepers in a population-based sample of women.
2. Methods In this population-based study (‘‘Sleep and Health in women’’) [20], a questionnaire on sleeping habits and somatic disorders
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was sent to women aged P20 years, randomly selected from the population registry of the city of Uppsala, Sweden The response rate was 71.6% (n = 7051). The final study population included the 6461 non-pregnant women who had reported their sleep duration and waist circumference. The questionnaire consisted of 109 questions and has previously been described in detail [20]. Briefly, the questionnaire comprised questions on sleep duration, snoring habits, insomnia, occupational status, shift work, civil status, physical activity, smoking, alcohol dependence, and anxiety and depression. To assess sleep duration (h/night) the women were asked ‘‘How many hours do you on average sleep during the night?’’ Sleep duration was grouped by hours slept but was also classified into three categories: short sleepers (<6 h/night), normal sleepers (6–<9 h/night), and long sleepers (P9 h/night). In conjunction with the questionnaire, the women were given a tape measure and instructions on how to measure their waist circumference [20]. A waist circumference P88 cm was used to define central obesity according to NCEP (National Cholesterol Education Program) criteria [21]. BMI was calculated from self-reported height and weight. Six questions assessed smoking habits. Based on the participants’ responses they were categorized as ‘‘current smokers,’’ ‘‘ex-smokers’’ (i.e., had quit smoking at least six months before answering the questionnaire), or ‘‘non-smokers’’ (i.e., never smoked). Alcohol dependence was assessed by the CAGE (acronym for cut down, annoyed by criticism, guilty about drinking, and eye-opener drinks) alcohol and screening questionnaire [22]. Psychological distress was assessed using the Hospital Anxiety and Depression (HAD) scale [23]. The participants’ physical activity was analyzed by four questions adopted from a questionnaire used in a large population-based study on the correlation of physical activity and mortality [24]. Occupational status was categorized into the following categories: working full-time (P30 h/week), working part time (<30 h/ week)/working at home, student, unemployed, sick leave/early retirement. The participants were also asked to ascertain how many months they had been working nights or shifts over the past 10 years. A cut-off point of 60 months was chosen when analyzing working nights or shifts as risk factors for EDS and fatigue. Civil status was classified into two categories: married/living together and single (including divorced and widowed women). The women were asked if they had any somatic disease(s) that required regular medical attention. Somatic diseases were: asthma/chronic obstructive pulmonary disease (COPD), cardiovascular disease, diabetes, gastric ulcer/reflux, back/joint problems, fibromyalgia, gynecological problems and neurological problems. In addition, the women were asked if they were taking any medication on a regular basis. Medication was indicated if taking any of the following: beta blockers, beta 2 agonists, diabetes medication, or benzodiazepines/sleep medicine as these were considered to potentially affect sleep or obesity.
3. Statistical analyses Statistical analyses were performed using Stata 10 (Stata Corporation, College Station, TX, USA). Univariate analyses were conducted using the unpaired t-test for continuous variables and the chi-squared test for categorical variables to compare the sleep duration groups. All significant variables from the univariate analyses were then entered into a multiple model, which was performed using logistic regression with central obesity as a dependent variable. The results from the logistic regression are presented as adjusted odds ratios (ORs) with 95% confidence intervals (95% CI).
Associations between sleep duration and central obesity (waist circumference) were analyzed using a multiple regression analysis. Results from the regression analysis are presented as adjusted b-values with p-values. To analyze the presence of a U-shaped relationship between sleep duration and central obesity the squared sleep duration was entered into the multiple regression analysis. A two-sided p-value < 0.05 was considered a statistically significant result. In a previous study we have seen that short sleep duration has most importance in younger women (age < 50 years) [19] and, in addition, there was a significant interaction between age and sleep duration (p = 0.014) for central obesity. Therefore, the population was divided by age above and below 50 years in some analyses. The study was approved by the Ethics Committee of the Medical Faculty at Uppsala University and all participants gave their informed consent before participating.
4. Results Compared with normal sleepers (6–<9 h), both short sleepers and long sleepers were more centrally obese and had greater neck and waist circumference and short sleepers were even more centrally obese than long sleepers. Both short and long sleepers were more physically inactive, more likely to be smokers, had an illness, or were taking medication, and more often suffered from psychological distress compared with normal sleepers. In addition, both short sleepers and long sleepers were more often married or living with someone and were more often sick leaved or retired early. In contrast, compared with normal sleepers, short sleepers were older and had higher BMI, whereas there were no differences for the long sleepers. Long sleepers, on the other hand, were more often students or seeking employment compared with normal sleepers short sleepers. When further comparing short sleepers with long sleepers, the short sleepers were more seldom alcohol dependent and were more often suffering from physical illness and also from psychological distress. There were also differences in occupational status as short sleepers were more often working full-time and also part-time, but also more often on sick-leave or early retirement than long sleepers (Table 1). In younger women (age < 50 years), both short sleepers and long sleepers shared many of the same characteristics as in the whole group. However, increased neck circumference (33.1 ± 3.6 versus 32.7 ± 2.5 cm; p = 0.011) and waist circumference (84.1 ± 14.7 versus 80.3 ± 10.9 cm; p < 0.0001) were seen only in short sleepers in the younger age group. Short sleepers were also older (36.6 ± 8.5 versus 33.4 ± 8.9 years; p < 0.0001). As in the whole population, long sleepers in the younger age group were more seldom working full-time (19.0% versus 42.8%; p < 0.0001) and were more often students (41.7% versus 25.5%; p < 0.0001) or seeking employment (7.4% versus 2.4%; p < 0.0001) compared with normal sleepers (6–<9 h). Furthermore, long sleepers were also younger (29.4 ± 8.6 versus 33.4 ± 8.9; p < 0.0001) and more often living with someone (41.9% versus 33.0%; p = 0.011) compared with normal sleepers. In comparison with long sleepers, short sleepers in the younger age group were older (36.6 ± 8.5 versus 29.4 ± 8.9 years; p < 0.0001), had greater waist circumference (84.1 ± 14.7 versus 81.0 ± 13.0 cm; p = 0.016), higher BMI (24.5 ± 5.0 versus 23.5 ± 4.3 cm; p = 0.024), and were more likely to be smokers (28.2% versus 22.7%; p = 0.026). In addition, the short sleepers were more often suffering from physical illness (25.6% versus 18.0%; p = 0.036), anxiety, and depression (31.4% versus 14.5%; p < 0.0001) and were more often working full-time (43.5% versus 19.0%; p < 0.0001), on sick-leave or early retired (10.4% versus 7.8%; p < 0.0001), and there were also more shift workers among the short sleepers (8.3% versus 3.2%; p = 0.042).
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J. Theorell-Haglöw et al. / Sleep Medicine 13 (2012) 1079–1085 Table 1 Characteristics of the study population. Normal sleepers 6–<9 h (n = 5661)*
Short sleepers <6 h (n = 859)*
Sleep duration (h) Central obesity (P88 cm) Neck circumference Waist circumference BMI (kg/m2)
6.9 ± 1.2 33.3 33.5 ± 2.9 84.0 ± 12.8 24.1 ± 4.1
N/A 31.3 33.4 ± 2.8 83.4 ± 12.2 24.0 ± 4.0
N/A 43.2 34.1 ± 33.9 87.4 ± 15.0 24.9 ± 4.6
BMI (group) <20 20-<25 25–<30 P30
11.1 55.3 24.1 9.4
11.2 57.0 23.4 8.4
9.8 48.2 28.3 13.7
Snoring
7.7
7.4
8.4
p Value
<0.0001 <0.0001 <0.0001 <0.0001
Long sleepers P9 h (n = 351)* N/A 38.5 34.0 ± 3.3 85.3 ± 14.1 24.3 ± 4.5
<0.0001
Physical activity High Medium Low
19.4 61.7 18.9
20.7 62.0 17.3
12.7 61.2 26.2
Smoking Non smoker Ex-smoker Current smoker Alcohol dependency Physical illness Medication
60.5 22.4 17.1 6.0 22.1 12.0
61.3 22.4 16.3 5.8 19.2 9.8
55.9 24.3 19.8 5.7 37.8 21.7
Psychological distress None Anxiety Depression Anxiety and depression
63.6 22.2 3.4 10.8
66.6 21.6 3.2 8.7
46.8 26.1 4.3 22.8
0.32
9.8
<0.0001
0.96 <0.0001 <0.0001
57.0 20.1 22.9 9.6 29.3 17.4
<0.0001
34.6
33.1
40.9
46.1 18.1 18.9 2.6 5.0
47.5 18.6 19.2 2.4 3.5
47.5 16.7 10.8 2.5 12.3
Working shifts
4.2
4.4
4.8
Short versus Long sleepers p Value
0.007 0.0002 0.005 0.21
N/A 0.15 0.62 0.035 0.024
0.002
0.067
0.10
0.44
0.001
0.22
0.006
0.21
0.004 <0.0001 <0.0001
0.020 0.005 0.094
0.003
<0.0001
0.001 <0.0001
0.86 <0.0001
0.15
0.002
16.5 58.6 24.9 0.007
Married/living together Occupation Full-time Part-time/working at home Student Seeking employment Sick-leave/early retirement
p Value
14.8 48.2 24.8 12.3
59.7 21.5 4.9 13.9 <0.0001 <0.0001
41.5 21.1 13.9 32.1 7.1 11.8
<0.0001
2.3
All values are indicated as % or mean ± SD.
In women above 50 years, both short sleepers and long sleepers shared some of the same characteristics as in the whole population, but, in addition, they were older (65.1 ± 10.7 versus 62.6 ± 10.2 years; p = 0.006) and were more seldom working full-time (28.1% versus 60.7%; p < 0.0001) compared with normal sleepers (6–<9 h). A low level of physical activity compared with normal sleepers (28.6% versus 20.5%; p < 0.0001) was seen only in short sleepers in women above 50 years and short sleepers were also more seldom snorers (8.1% versus 11.9%; p = 0.018) and more seldom shift workers (1.96% versus 2.01%; p = 0.011). Long sleepers had greater neck (35.4 ± 2.8 verses 34.5 ± 2.8 cm; p = 0.0005) and waist (91.9 ± 13.1 versus 88.4 ± 12.5 cm; p = 0.002) circumference and were more often alcohol dependent (6.5% versus 2.3%; p = 0.004) compared with normal sleepers. Long sleepers in comparison with short sleepers in the older age group had narrower neck circumference (34.8 ± 3.0 verses 35.4 ± 2.8 cm; p = 0.030) and were more seldom snorers (8.1% versus 14.5%; p = 0.030). In addition, short sleepers were more seldom smokers (14.1% versus 23.3%; p = 0.013) and alcohol dependent (2.6% versus 6.5%; p = 0.037) compared with long sleepers. However, short sleepers were more often suffering from anxiety (23.9% versus 11.9%; p = 0.022) or both anxiety and depression (16.8% versus 12.7%; p = 0.022) when compared with long sleepers. Furthermore, short sleepers in the older age group were more often working full-time (53.0% versus 28.1%; p = 0.007) and were more seldom on sick-leave or early retired (15.0% versus 25.0%; p = 0.007) compared to long sleepers.
5. Associations with central obesity Using the squared sleep duration there was a U-shaped relationship between reported sleep duration and waist circumference (p < 0.0001 for comparison with a linear relationship; Fig. 1). Also this relationship remained when adjusting for confounders (p = 0.003 for comparison with a linear relationship; Table 2). A mean difference of six centimeters in waist circumference was seen between women sleeping <5 h and those sleeping 7–<8 h. In addition, there was also
92 Waist circumference (cm)
*
All women (n = 6871)*
90 88 86 84 82 80 <5h n=253
5-<6h n=606
6-<7h n=1,703
7-<8h n=2,484
8-<9h n=1,474
9-<10h n=276
>=10h n=75
Sl Sleep d duration ti (h (hours)) Fig. 1. Waist circumference in relation to sleep duration. Results are presented as mean ± SE.
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Table 2 Associations between sleep duration and waist circumference. Waist circumference All (n = 5773)
*
<50 years (n = 3625)
P50 years (n = 2148)
Adj. b (95% CI)*
p Value
Adj. b (95% CI)*
p Value
Adj. b (95% CI)*
p Value
Sleep duration (h) Squared sleep duration (h2) Age (years) Snoring
2.81 ( 4.58 to 1.04) 0.19 (0.064–0.32) 0.22 (0.20–0.24) 6.85 (5.71–7.99)
0.002 0.003 <0.0001 <0.0001
3.22 ( 5.77 to 0.68) 0.21 (0.33–0.40) 0.25 (0.21–0.29) 7.17 (5.54–8.81)
0.013 0.020 <0.0001 <0.0001
2.96 ( 5.54 to 0.38) 0.21 (0.025–0.40) 0.18 (0.12–0.24) 6.38 (4.73–8.03)
0.025 0.027 <0.0001 <0.0001
Physical activity High Medium Low
Reference 3.10 (2.32–3.87) 5.84 (4.82–6.85)
<0.0001 <0.0001
2.83 (2.00–3.67) 5.60 (4.44–6.76)
<0.0001 <0.0001
3.61 (1.71–5.50) 6.49 (4.29–8.69)
<0.0001 <0.0001
Smoking Non smoker Ex-smoker Current smoker
Reference 1.009 (027–1.74) 0.23 ( 1.06 to 0.59)
0.007 0.58
1.17 (0.22–2.13) 0.28 ( 0.71 to 1.28)
0.016 0.58
0.42 ( 0.79 to 1.63) 1.60 ( 3.10 to 0.90)
0.50 0.038
Alcohol dependency
0.38 ( 0.88 to 1.64)
0.55
0.40 ( 0.92 to 1.71)
0.56
0.56 ( 2.78 to 3.91)
0.74
Psychological distress None Anxiety Depression Anxiety and depression
Reference 1.55 ( 2.92 to 0.82) 0.61 ( 1.09 to 2.32) 0.34 ( 0.69 to 1.36)
1.05 ( 1.88 to 0.22) 3.00 (0.67–5.35) 0.21 ( 1.00 to 1.42)
0.013 0.012 0.73
2.50 ( 3.98 to 1.02) 1.69 ( 4.25 to 0.87) 0.60 ( 1.28 to 2.47)
0.001 0.20 0.53
Working shifts
1.30 ( 0.28 to 2.80)
2.05 (0.46–3.64)
0.011
2.45 ( 6.21 to 1.31)
0.20
<0.0001 0.48 0.52 0.09
Adjusted for all the variables in the table.
a difference of six centimeters between the group sleeping P10 h and women sleeping 7–<8 h (Fig. 1). In addition, habitual snoring,
medium or low levels of activity and anxiety were all independently associated with waist circumference (Table 2).
Table 3 Multiple analyses for women below and above age 50 years. Central obesity (waist circumference P88 cm) Age <50 years (n = 3625)
*
Age P50 years (n = 2148)
Unadj. OR (95% CI)
p Value
Adj. OR (95% CI)*
Short sleep duration (<6 h) Normal sleep duration (6–<9 h) Long sleep duration (P9 h) Age (years) Snoring
1.83 1.0 1.39 1.06 3.82
(1.43–2.34)
<0.0001
(1.01–1.91) (1.05–1.07) (2.86–5.10)
0.044 <0.0001 <0.0001
1.36 1.0 1.20 1.04 3.11
Physical activity High Medium Low
1.0 2.41 (1.95–2.97) 4.04 (3.15–5.17)
Smoking Non smoker Ex-smoker Current smoker
p Value
Unadj. OR (95% CI)
(1.02–1.82)
0.036
(0.82–1.76) (1.03–1.06) (2.25–4.31)
0.34 <0.0001 <0.0001
1.05 1.0 1.36 1.03 2.05
<0.0001 <0.0001
1.0 1.87 (1.49–2.35) 3.28 (2.49–4.33)
1.0 1.58 (1.30–1.90) 1.61 (1.33–1.96)
<0.0001 <0.0001
Alcohol dependency Physical illness Medication
0.97 (0.74–1.28) 1.89 (1.54–2.31) 1.64 (1.21–2.22)
Psychological distress None Anxiety Depression Anxiety and Depression
p Value
Adj. OR (95% CI)*
p Value
(0.64–1.25)
0.51
(0.96–3.41) (1.03–1.09) (1.57–3.09)
0.064 <0.0001 <0.0001
(0.86–1.29)
0.63
(0.95–1.94) (1.02–1.04) (1.59–2.65)
0.095 <0.0001 <0.0001
0.89 1.0 1.81 1.06 2.19
<0.0001 <0.0001
1.0 1.89 (1.40–2.54) 3.41 (2.45–4.75)
<0.0001 <0.0001
1.0 1.56 (1.05–2.33) 2.01 (1.25–3.23)
0.028 0.004
1.0 1.26 (1.02–1.56) 1.15 (0.92–1.44)
0.030 0.23
1.0 1.00 (0.84–1.19) 0.91 (0.73–1.13)
0.98 0.38
1.0 1.31 (1.0008–1.71) 1.13 (0.83–1.55)
0.049 0.44
0.85 <0.0001 0.001
1.02 (0.74–1.40) 1.34 (1.04–1.76) 0.93 (0.63–1.38)
0.89 0.027 0.73
1.21 (0.73–1.99) 1.72 (1.47–2.02) 1.75 (1.45–2.11)
0.46 <0.0001 <0.0001
1.15 (0.61–2.15) 1.43 (1.07–1.92) 1.52 (1.46–2.22)
0.67 0.017 0.028
1.0 0.74 (0.62–0.90) 2.02 (1.30–3.13) 1.30 (1.03–1.64)
0.002 0.002 0.028
1.0 0.73 (0.59–0.90) 1.21 (0.74–1.99) 0.95 (0.73–1.25)
0.003 0.45 0.72
1.0 0.68 (0.54–0.85) 1.07 (0.74–1.57) 1.07 (0.82–1.41)
0.001 0.72 0.62
1.0 0.47 (0.34–0.67) 1.01 (0.54–1.88) 0.72 (0.47–1.10)
<0.0001 0.97 0.12
Married/living together
0.78 (0.66–0.92)
0.003
1.09 (0.90–1.32)
0.38
1.29 (1.10–1.51)
0.002
1.15 (0.86–1.52)
0.34
Occupation Full-time Part-time/working at home Student Seeking employment Sick-leave/early retirement
1.0 1.29 0.52 1.95 3.32
1.0 1.26 0.92 2.25 2.07
0.035 0.56 0.001 0.002
1.0 1.39 1.73 1.73 2.47
1.0 1.35 2.22 1.89 1.96
0.081 0.15 0.089 0.002
Working shifts
1.40 (1.02–1.93)
0.36
0.65 (0.35–1.18)
(1.06–1.57) (0.42–0.65) (1.28–2.98) (2.25–4.90)
Adjusted for all the variables in the table.
0.011 <0.0001 0.002 <0.0001 0.038
(1.02–1.57) (0.71–1.20) (1.37–3.69) (1.29–3.32)
1.18 (0.83–1.67)
(1.03–1.86) (0.68–4.40) (0.90–3.32) (1.74–3.51)
0.030 0.25 0.10 <0.0001 0.16
(0.96–1.89) (0.75–6.57) (0.91–3.95) (1.29–2.99)
0.72 (0.35–1.48)
0.37
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Fig. 2. Associations between short sleep duration (sleep time <6 h) and central obesity (waist circumference >88 cm) by age groups. Results are presented as adjusted OR’s with 95% CI after adjusting for physical activity, alcohol dependency, psychological distress, physical illness, taking medication, marital status, occupation, and working shifts.
In the unadjusted analysis in women <50 years both short and long sleep duration were shown as risk factors for central obesity. In addition, age, physical inactivity, smoking status, physical illness, medication, psychological distress, and several socioeconomic factors were associated with central obesity. Having anxiety alone showed a reduced risk of central obesity. When adjusting the model for confounders, short sleep duration remained a risk factor for central obesity, whereas long sleep duration did not reach statistical significance. In addition, age, physical inactivity, ex-smoking, and physical illness was all still associated with central obesity. Furthermore, occupational factors remained significantly associated with central obesity. Anxiety still reduced the risk of central obesity (Table 3). In women above 50 years, neither short nor long sleep duration were risk factors for central obesity, although there was a trend for an association with long sleep duration. However, age, physical inactivity, physical illness, medication, and socioeconomic factors were shown to be associated with central obesity. Having anxiety alone also showed a reduced risk of central obesity also in this age group. In the adjusted model for women above 50 years of age, physical inactivity, physical illness, being on medication, being on sick-leave, or being early retired were all still associated with central obesity. Also, in this age group having anxiety showed a reduced risk of central obesity (Table 3). When further subdividing the younger women into age groups of 10 year intervals we found that the association between short sleep duration and central obesity decreased with increasing age. This decrease also remained when adjusting for confounders (Fig. 2).
6. Discussion This study showed that there were differences between short sleepers and long sleepers compared to normal sleepers. In addition, we showed a U-shaped association between sleep duration and central obesity. When adjusting for confounders, only the relationship between short sleep and central obesity remained. Further-
more, the association between short sleep duration and central obesity was strongest in younger women. In unadjusted analyses both short and long sleep duration were associated with central obesity in younger women. Short sleep duration further remained associated with central obesity after adjusting for potential confounders in the younger women. However, there was no relationship between sleep duration and central obesity in the women P50 years. Several studies have analyzed the relation between self-reported sleep duration and obesity by measuring BMI [7–10,25,26], weight [5], or weight gain over time [5,6,27]. Both short [26,28–30] and long sleep duration have been associated with higher risk of obesity [25], and the optimal sleep duration has been suggested to be 7 h per night in both males and females, as this is the sleep duration where optimal BMI is seen [31]. A U-shaped association between self-reported sleep duration and BMI was shown in a large sample of middle-aged men and women independent of age and sex [9]. Two studies showing a U-shaped association in unadjusted data did, however, not show the curve linear relationship when adjusting for confounders, although the relationship between short sleep duration and BMI was still significant after controlling for confounders [6,10]. This is consistent with the results from the present study where a relationship with central obesity was seen for short sleep duration. Some previous studies have performed age-divided analyses. In a longitudinal epidemiological study, Hairston et al. showed that self-reported short as well as long sleep duration increased BMI, subcutaneous adipose tissue, and visceral adipose tissue measured by CT scan in persons younger but not older than 40 years [32]. From the NHANES cohort, both men and women below but not above age 50 years showed an inverse relationship between short reported sleep duration and increased prevalence of overweight or obesity in univariate analyses [6]. Apart from sleep duration several factors were associated with central obesity in the current study. In both women below and above 50 years of age, medium or low levels of physical activity, physical illness, or being on sick-leave or early retired were shown to be associated with central obesity. Having anxiety alone showed
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a reduced risk of central obesity. The association between low socioeconomic status and health has been suggested to be mediated by short sleep, and it has been shown that state of sleep debt is associated with decreased glucose tolerance, increased evening cortisol, and increased sympathetic activity [37]. Further, the relationship between long work hours and obesity has also been shown to be mediated by short sleep duration [38]. The present study further showed that, although short sleepers and long sleepers shared many of the same characteristics, there were also differences between them as short sleepers were older and had higher BMI, whereas long sleepers were more often students or seeking employment. Also, when dividing the women into age groups (over and under 50 years), there were differences between short sleepers and long sleepers. In the younger women short sleepers compared with normal sleepers were older and had greater neck and waist circumference as well as BMI and they more often suffered from psychological distress. As in the whole population, long sleepers were more often students or unemployed. In women above the age of 50 years, short sleepers were more seldom snorers, were more often physically inactive, and were more seldom shift workers compared with normal sleepers. The long sleepers in women P50 years had greater neck and waist circumference compared with normal sleepers. Few earlier studies on factors relating to short and long sleep duration have been performed in an adult population-based sample. However, in a community-based study, Park and co-workers [18] showed that both short and long sleep duration (<5 and P9 h, respectively) was correlated with unemployment, physical illness, anxiety, and also alcohol dependency. Short sleep duration was further associated with being single and being obese, whereas long sleep duration was associated with younger age and also underweight [18], a result in discrepancy with the results from the present study. Unfortunately, there were no age divided analyses performed [18]. From the Nurses Health Study use of antidepressants or benzodiazepines as well as some physical illnesses were strongly correlated with prolonged sleep [16]. Short sleep duration and sleep disturbances have been linked to several physical illnesses such as diabetes [33], hypertension [34] and the metabolic syndrome [35]. In addition, short sleep duration has also been associated with mortality risk in women [36]. In the present study both short and long sleep duration were associated with physical illness; however, in women P50 years, there was only a significant association between short sleep duration and physical illness. This study was conducted in a large population of women and had a high response rate. Nonetheless, there are some limitations to consider when interpreting the results. All the data are selfreported. However, for 400 of the women waist circumference was measured objectively two years later. In spite of the time lapse between the two measures there was good correlation between the two measures (b = 0.85; p < 0.0001). Also, as the study is cross-sectional, causality is difficult to infer. Furthermore, the fact that the study only included women may limit the generalizability of our results. In conclusion, there are differences between short sleepers and long sleepers compared to normal sleepers. Furthermore, we show an association between short sleep duration and central obesity when adjusting for confounders. This association was strongest in younger women and, therefore, it is important to identify short sleepers, especially in younger women.
Conflict of interest The ICMJE Uniform Disclosure Form for Potential Conflicts of Interest associated with this article can be viewed by clicking
on the following link: http://dx.doi.org/10.1016/j.sleep.2012. 06.013.
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