Abstract
Objectives:
The aim of this study is to examine the relationship between self-reported sleep duration and arterial stiffness in a large-scale Japanese study.
Design:
Cross-sectional study.
Setting:
Sapporo City, Hokkaido, Japan.
Participants:
Local government employees aged 35-62 years, who underwent annual health checkups from April 2003 to March 2004. After excluding those with incomplete data, data from 4,268 employees (males: 3,410) participants were analyzed.
Interventions:
N/A.
Measurements and Results:
Brachial-ankle pulse-wave velocity (baPWV) was investigated as an indicator of arterial stiffness. We used a self-administered questionnaire, which included items on daily sleep duration, lifestyle factors, and occupational factors. Sleep duration was classified into 5 categories; “ ≤ 5 h,” “6 h,” “7 h,” “8 h,” and “ ≥ 9 h.” Results of multiple linear regression analysis after fully adjusting the model revealed that subjects with ≥ 9 h of daily sleep had significantly elevated baPWV values compared with the reference group with 7 h of sleep. Stratified analyses by sex showed that there was a significant association among male subjects only.
Conclusions:
Daily sleep duration ≥ 9 h was found to be associated with elevated values of baPWV. This suggests that there is an association between long sleep duration and arterial stiffness.
Citation:
Yoshioka E; Saijo Y; Kita T; Okada E; Satoh H; Kawaharada M; Kishi R. Relation between self-reported sleep duration and arterial stiffness: a cross-sectional study of middle-aged Japanese civil servants. SLEEP 2011;34(12):1681-1686.
Keywords: Daily sleep duration, arterial stiffness, Brachial-ankle pulse-wave velocity, cardiovascular disease
INTRODUCTION
Recently, a large number of epidemiological studies have reported that either long or short sleep duration is independently associated with cardiovascular disease.1–12 However, the specific mechanisms underlying the association between habitual sleep duration and cardiovascular disease remain unclear.
Many noninvasive methods to measure arterial stiffness are available.13 Pulse-wave velocity (PWV) is a known indicator of arterial stiffness, and elevated PWV is associated with the development of atherosclerotic diseases.14–17 In Japan, although there has been no prospective study on elevated PWV and the incidence of CVD, elevated PWV has been significantly related with death from cardiovascular disease in Japanese-Americans living in Hawaii.18 A simple noninvasive automatic method for measuring brachial-ankle PWV (baPWV) has recently been developed.19,20 The technical simplicity and short sampling time of the new method makes it more feasible for use in population-based screening compared to previous methods, such as carotid-femoral PWV. One report has been published on the association between daily sleep duration and degree of arterial stiffness.10 However, the relation between sleep duration and increased arterial stiffness using PWV has not yet been examined.
The aim of this study is to examine the relationship between self-reported sleep duration and elevated baPWV as a marker of arterial stiffness in a large-scale Japanese study. Since daily sleep duration represents a potentially modifiable condition, clarifying the effect of sleep duration on arterial stiffness and new cardiovascular disease markers, such as baPWV, could facilitate efforts to develop more effective preventive measures. In addition, because of its practicality and risk predictive ability, baPWV should be introduced in population-based screening.
METHODS
Study Population
Subjects were local government employees (n = 10,423) in Sapporo City, aged 35-62 years, who underwent an annual health check-up between April 2003 and March 2004. We used a self-administered questionnaire, which included items on daily sleep duration, clinical history, family history, smoking, alcohol consumption, exercise frequency, educational background, and occupational circumstances. The questionnaire was distributed to subjects before their annual health check-up and collected during it. Completed questionnaires and written informed consent to view health check-up data were obtained from 5,013 subjects (response rate = 48.1%).
A total of 745 subjects were excluded for the following reasons: PWV not measured (n = 613), blood samples not analyzed (n = 1), missing data for sleep duration (n = 1), low ankle/brachial pressure index (< 0.9; n = 11; baPWV values in subjects with peripheral artery disease could not be evaluated accurately), or past history of coronary disease or stroke (n = 119). The final study group thus comprised 4268 subjects.
This study was conducted with the written informed consent of all subjects and was approved by the institutional ethical board for epidemiological studies of Hokkaido University Graduate School of Medicine.
Assessment of Sleep Duration
We obtained information on average daily sleep duration during the preceding month, which was then classified into the following 5 categories: ≤ 5 h (< 5.5 h); 6 h (5.5 to < 6.5 h); 7 h (6.5 to < 7.5 h); 8 h (7.5 to < 8.5 h); and ≥ 9 h (≥ 8.5 h). Fractional hours were rounded off.
Outcomes
A volume-plethysmographic device was used to measure baPWV (Form PWV/AVI; model BP-203RPEII, Colin Co., Komaki, Japan).20 This device records a phonocardiogram, electrocardiogram, and volume pulse form and arterial blood pressure at the left and right brachia and bilateral ankles. A time-phase analysis between right brachial and volume waveforms at both ankles was used for calculating baPWV. Blood pressure, heart rate (HR) and ankle brachial index (ABI) were measured using a pulse-wave velocimeter concurrently with PWV measurement. ABI is the ratio of ankle systolic blood pressure to brachial systolic blood pressure; right and left ABIs were measured simultaneously. In all studies, baPWV was obtained after ≥ 5 min of rest.
Covariates
Anthropometric measures (height, body weight) were recorded using a standardized protocol. Body mass index (BMI) was calculated as weight (kg)/height (m2). Blood samples were drawn from the antecubital vein of the seated subject with minimal tourniquet use after a 12-h fast. Specimens were collected in siliconized glass vacuum tubes containing sodium fluoride for blood glucose. Total cholesterol (TC) levels were measured using an enzymatic method (Wako, Osaka, Japan). Triglyceride (TG) levels were measured using an enzymatic method (Daiichi Pure Chemicals, Tokyo, Japan), high-density lipoprotein cholesterol (HDL-C) levels by a direct method (Daiichi Pure Chemicals), and blood glucose by an amperometric method (Arkray, Kyoto, Japan).
Educational background was categorized into “high school education or less” or “more than high school.” Frequency of leisure time exercise (with perspiration) was categorized into “rarely or never,” “1-2 times per week,” or “3 times per week or more.” Smoking status was categorized into “nonsmoker” (never smoked), “ex-smoker,” or “current smoker.” Alcohol consumption was categorized into “rarely or never,” “1-5 times/week,” or “6-7 times/week.”
Occupation was categorized into “non-manual workers” or “manual workers.” Non-manual workers included clerical workers, professional workers (e.g., physicians, nurses, public health nurses, pharmacists, radiographers, dieticians, researchers, and technicians), and fire fighters. Manual workers included drivers, subway conductors, sanitation workers, cooks, and janitors. Working hours were calculated as average working hours including overtime work per week, during the previous month, and were classified as “ < 40 hours per week,” “40-50 hours per week,” “50-60 hours per week,” and “ ≥ 60 hours per week.” The number of days off was also calculated as days off per month during the previous month. Occupational stress was assessed using the demand-control model (DCM). The Japanese version of the DCM consists of 5 questions on psychological demands (job demands, time pressures, and conflicting demands) and 6 questions on decision latitude (influence or control over work, job variety, and the possibilities for learning new skills).21 Each question has 4 frequency-based response categories ranging from “never” (1 point) to “always” (4 points). Job strain was defined as the ratio of demands to job control.22 Cronbach α coefficients were 0.64 for job control, and 0.75 for job demand.
Statistical Analysis
First, differences in the distribution of variables by daily sleep duration were tested for statistical significance with the Kruskal-Wallis test for continuous variables or χ2 test for categorical variables. Next, to investigate the association between daily sleep duration and mean baPWV, we performed multiple linear regression analyses using the following models: crude; adjusted for age and sex; model 1: adjusted for age, sex, and systolic blood pressure; model 2: adjusted for model 1 variables plus medication for hypertension; model 3: adjusted for model 2 variables plus HR; model 4: adjusted for model 3 variables plus biological risk factors (BMI, TC, log TG, HDL-C, and fasting blood sugar); model 5: adjusted for model 4 variables plus lifestyle factors (educational background, frequency of exercise, smoking status, and alcohol consumption); model 6: adjusted for model 5 variables plus occupational factors (occupation, working hours, shift work, number of days off, and job strain). Finally, we performed multiple linear regression analyses for men and women separately and adjusted for age, biological factors, lifestyle factors, and occupational factors.
For all analyses, statistical significance was defined as a 2-tailed P-value < 0.05. All analyses were conducted using SPSS software version 18 for Macintosh (SPSS Inc., Chicago, USA).
RESULTS
Characteristics of participants are reported in Table 1 by categories of sleep duration. Longer sleep duration was associated with higher PWV, being male, older age, higher systolic blood pressure, taking medication for hypertension, more frequent alcohol consumption (6-7 times/week), shorter working hours (< 40 h), larger numbers of days off, and lower scores of job strain. Compared with subjects sleeping 7 h, those sleeping ≥ 9 h were less educated, had more frequent exercise habits (≥ 3 times/week) and tended to be manual workers; while those with ≤ 5 h were more educated and tended to be shift workers. Subjects with 8 h of sleep had the highest TG levels. The proportion of current smokers was smallest among those with 7 h of sleep.
Table 1.
Characteristics of subjects by sleep duration
| N | Total | Sleep Duration Per Day |
P valueb | |||||
|---|---|---|---|---|---|---|---|---|
| ≤ 5 h | 6 h | 7 h | 8 h | ≥ 9 h | ||||
| Number | 4268 | 333 | 1205 | 1865 | 775 | 90 | ||
| baPWV (cm/s) | 4268 | 1345 ± 202 | 1301 ± 190 | 1321 ± 191 | 1346 ± 194 | 1386 ± 215 | 1465 ± 312 | < 0.001 |
| Sex | 4268 | |||||||
| Men | 3410 (79.9%) | 236 (70.9%) | 874 (72.5%) | 1535 (82.3%) | 681 (87.9%) | 84 (93.3%) | < 0.001 | |
| Women | 858 (20.1%) | 97 (29.1%) | 331 (27.5%) | 330 (17.7%) | 94 (12.1%) | 6 (6.7%) | ||
| Age | 4268 | 48.0 ± 6.9 | 45.8 ± 7.3 | 47.2 ± 6.8 | 48.2 ± 6.9 | 49.6 ± 6.7 | 50.1 ± 6.9 | < 0.001 |
| SBP (mm Hg) | 4262 | 121.1 ± 15.7 | 117.3 ± 14.0 | 119.6 ± 15.5 | 121.6 ± 15.7 | 123.5 ± 16.0 | 127.6 ± 18.4 | < 0.001 |
| HR | 4268 | 60.4 ± 9.2 | 60.0 ± 8.5 | 60.4 ± 9.2 | 60.3 ± 9.2 | 60.8 ± 9.6 | 61.6 ± 9.2 | 0.443 |
| BMI | 4267 | 23.4 ± 3.1 | 23.3 ± 3.5 | 23.5 ± 3.1 | 23.4 ± 3.0 | 23.5 ± 3.0 | 23.5 ± 3.6 | 0.811 |
| Total Cholesterol (mg/dL) | 4268 | 207.6 ± 33.1 | 206.9 ± 33.3 | 208.7 ± 32.8 | 206.8 ± 32.3 | 208.3 ± 34.5 | 204.3 ± 41.0 | 0.404 |
| Triglyceride (mg/dL)a | 4268 | 99.0 (97.4, 100.6) | 95.1 (89.3, 101.3) | 96.7 (93.7, 99.8) | 98.2 (95.9, 100.6) | 106.5 (102.5, 110.6) | 98.3 (87.4, 110.7) | 0.001 |
| HDL Cholesterol (mg/dL) | 4268 | 59.3 ± 15.4 | 59.4 ± 16.0 | 60.3 ± 15.9 | 59.1 ± 15.1 | 58.1 ± 15.0 | 60.5 ± 16.9 | 0.034 |
| Fasting Glucose (mg/dL) | 4268 | 94.4 ± 20.1 | 93.4 ± 21.5 | 93.6 ± 20.3 | 94.3 ± 18.9 | 96.4 ± 22.2 | 94.9 ± 15.2 | 0.038 |
| Medication for Hypertension | 4268 | |||||||
| Yes | 356 (8.3%) | 18 (5.4%) | 93 (7.7%) | 153 (8.2%) | 79 (10.2%) | 13 (14.4%) | 0.015 | |
| No | 3912 (91.7%) | 315 (94.6%) | 1112 (92.3%) | 1712 (91.8%) | 696 (89.8%) | 77 (85.6%) | ||
| Educational Background | 4268 | |||||||
| >High school | 1937 (45.4%) | 171 (51.4%) | 560 (46.5%) | 888 (47.6%) | 297 (38.3%) | 21 (23.3%) | < 0.001 | |
| ≤ High school | 2331 (54.6%) | 162 (48.6%) | 645 (53.5%) | 977 (52.4%) | 478 (61.7%) | 69 (76.7%) | ||
| Frequency of Exercise | 4262 | |||||||
| Rarely or never | 2437 (57.2%) | 200 (60.2%) | 749 (62.2%) | 1042 (56.0%) | 393 (50.8%) | 53 (59.6%) | < 0.001 | |
| 1-2 times/week | 1175 (27.6%) | 74 (22.3%) | 303 (25.1%) | 533 (28.3%) | 249 (32.2%) | 16 (18.0%) | ||
| 3 times/week or more | 650 (15.3%) | 58 (17.5%) | 153 (12.7%) | 287 (15.4%) | 132 (17.1%) | 20 (22.5%) | ||
| Smoking Status | 4268 | |||||||
| Non-smoker | 1381 (32.4%) | 121 (36.3%) | 431 (35.8%) | 622 (33.4%) | 182 (23.5%) | 25 (27.8%) | < 0.001 | |
| Ex-smoker | 983 (23.0%) | 52 (15.6%) | 247 (20.5%) | 443 (23.8%) | 220 (28.4%) | 21 (23.3%) | ||
| Current | 1904 (44.6%) | 160 (48.0%) | 527 (43.7%) | 800 (42.9%) | 373 (48.1%) | 44 (48.9%) | ||
| Alcohol Consumption | 4253 | |||||||
| Rarely or never | 1318 (31.0%) | 123 (36.9%) | 408 (34.0%) | 550 (29.6%) | 208 (26.9%) | 29 (32.2%) | < 0.001 | |
| 1-5 times/week | 1693 (39.8%) | 145 (43.5%) | 494 (41.2%) | 750 (40.4%) | 283 (36.6%) | 21 (23.3%) | ||
| 6-7 times/week | 1242 (29.2%) | 65 (19.5%) | 298 (24.8%) | 557 (30.0%) | 282 (36.5%) | 40 (44.4%) | ||
| Occupation | 4249 | |||||||
| Nonmanual workers | 3122 (73.5%) | 239 (73.1%) | 894 (74.3%) | 1415 (76.1%) | 534 (69.4%) | 40 (44.4%) | < 0.001 | |
| Manual workers | 1127 (26.5%) | 88 (26.9%) | 309 (25.7%) | 445 (23.9%) | 235 (30.6%) | 50 (55.6%) | ||
| Working Hours | 4263 | |||||||
| < 40 h | 613 (14.4%) | 30 (9.0%) | 155 (12.9%) | 278 (14.9%) | 129 (16.6%) | 21 (23.3%) | < 0.001 | |
| 40-50 h | 2650 (62.2%) | 151 (45.5%) | 694 (57.7%) | 1233 (66.1%) | 516 (66.6%) | 56 (62.2%) | ||
| 50-60 h | 638 (15.0%) | 78 (23.5%) | 230 (19.1%) | 244 (13.1%) | 79 (10.2%) | 7 (7.8%) | ||
| ≥ 60 h | 362 (8.5%) | 73 (22.0%) | 123 (10.2%) | 109 (5.8%) | 51 (6.6%) | 6 (6.7%) | ||
| Shiftwork | 4236 | |||||||
| Yes | 1013 (23.9%) | 114 (34.5%) | 295 (24.6%) | 373 (20.2%) | 206 (26.8%) | 25 (28.1%) | < 0.001 | |
| No | 3223 (76.1%) | 216 (65.5%) | 904 (75.4%) | 1477 (79.8%) | 562 (73.2%) | 64 (71.9%) | ||
| Number of Days Off | 4268 | 9.1 ± 2.2 | 8.6 ± 2.3 | 8.9 ± 2.2 | 9.2 ± 2.2 | 9.3 ± 2.2 | 9.8 ± 2.7 | < 0.001 |
| Job Strain | 4234 | 0.741 ± 0.184 | 0.797 ± 0.206 | 0.764 ± 0.192 | 0.725 ± 0.168 | 0.725 ± 0.187 | 0.713 ± 0.200 | < 0.001 |
Variables are presented as mean ± SD, geometric mean (95% CI) or number (percentage).
Log-transformed data were analyzed, and means (95% CI) were back-transformed.
Results of the Kruskal-Wallis test for continuous variables or the χ2 test for categorical variables are presented.
The results of multiple linear regression analyses for sleep duration and baPWV mean values are presented in Table 2. In the crude analysis, compared with subjects sleeping 7 h, those sleeping 8 h and 9 h or more had significantly elevated PWV, while those sleeping ' 5 h and 6 h had significantly lower PWV. After adjustment for age and sex, no statistical significance was found for those sleeping ≤ 5 h and 6 h. After adjustment for all possible confounders (biological factors, lifestyle and socioeconomic factors, or occupational factors), only those subjects sleeping ≥ 9 h had significantly elevated PWV.
Table 2.
Partial regression coefficients (PRC) (95% confidence interval) for the association between sleep duration and average baPWV (cm/s) before and after adjustment for the possible confounding factors
| N | Sleep Duration Per Day |
|||||
|---|---|---|---|---|---|---|
| ≤ 5 h | 6 h | 7 h | 8 h | ≥ 9 h | ||
| Crude | 4268 | -44.87 (-68.16, -21.59)*** | -24.82 (-39.29, -10.35)*** | Reference | 40.21 (23.48, 56.94)*** | 119.51 (77.27, 161.76)*** |
| Age and Sex Adjusted | 4268 | -6.16 (-27.18, 14.85) | -3.89 (-16.95, 9.17) | Reference | 19.65 (4.60, 34.70)* | 88.06 (50.14, 125.99)*** |
| Model 1 | 4262 | 9.37 (-6.40, 25.14) | 1.38 (-8.42, 11.18) | Reference | 12.83 (1.53, 24.12)* | 54.33 (25.87. 82.79)*** |
| Model 2 | 4262 | 9.17 (-6.56, 24.91) | 1.02 (-8.76, 10.80) | Reference | 12.72 (1.45, 23.99)* | 53.57 (25.17, 81.97)*** |
| Model 3 | 4262 | 8.67 (-6.52, 23.87) | -0.18 (-9.63, 9.26) | Reference | 11.27 (0.39, 22.16)* | 51.37 (23.94, 78.80)*** |
| Model 4 | 4261 | 8.42 (-6.44, 23.27) | 1.12 (-8.11, 10.34) | Reference | 9.03 (-1.59, 19.66) | 52.65 (25.88, 79.42)*** |
| Model 5 | 4246 | 7.46 (-7.40, 22.33) | -0.22 (-9.47, 9.03) | Reference | 9.62 (-1.05, 20.28) | 50.28 (23.45, 77.11)*** |
| Model 6 | 4163 | 4.74 (-10.60, 20.07) | -1.20 (-10.56, 8.15) | Reference | 8.22 (-2.55, 19.00) | 44.69 (17.69, 71.69)** |
Model 1: Adjusted for age, sex, and SBP. Model 2: Model 1 + Adjusted for hypertension. Model 3: Model 2 + Adjusted for HR. Model 4: Model 3 + Adjusted for biological risk factors (BMI, TC, log TG, HDL-C, and FBS). Model 5: Model 4 + Adjusted for lifestyle factors (education, exercise, smoking, and alcohol consumption). Model 6: Model 5 + Adjusted for occupational factors (occupation, working hours, shift work, days off, and job strain).
P < 0.05,
P < 0.01,
P < 0.001.
The results of multiple linear regression analyses by sex are presented in Table 3. Compared with subjects sleeping 7 h, those sleeping ≥ 9 h had significantly elevated PWV among male subjects, but not among female subjects.
Table 3.
Partial regression coefficients (PRC) (95% confidence interval) for the association between sleep duration and average baPWV (cm/s) by sex
| N | Sleep Duration Per Day |
|||||
|---|---|---|---|---|---|---|
| ≤ 5 h | 6 h | 7 h | 8 h | ≥ 9 h | ||
| Malea | 3339 | 6.13 (-12.29, 24.56) | -3.65 (-14.60, 7.31) | Reference | 6.12 (-5.78, 18.01) | 49.50 (20.79, 78.20)** |
| Femalea | 824 | 2.79 (-23.50, 29.09) | 6.90 (-10.37, 24.17) | Reference | 17.04 (-9.09, 43.18) | -80.28 (-178.15, 17.60) |
Adjusted for age, biological risk factors (BMI, SBP, HR, TC, log TG, HDL-C, FBS, and hypertension), lifestyle and socioeconomic factors (education, exercise, smoking, and alcohol consumption).work characteristics (position, working hours, shift work, days off, and job strain). *P < 0.05, **P < 0.01, ***P < 0.001.
DISCUSSION
Our results from Japanese civil servants indicate that, compared with the reference group of 7 hours of sleep, 9 hours or more is significantly associated with higher PWV. To the best of our knowledge, this investigation is the first to assess the association between sleep duration and PWV as a marker of arterial stiffness.
Imaging of carotid arterial walls by B-mode ultrasonography with measurement of intima-media thickness (IMT) is increasingly used as a noninvasive quantitative marker for cardiovascular disease. Wolff et al. reported that, compared with 8 hours sleep, both shorter (5 h) and longer (≥ 10 h) sleep durations are associated with higher carotid IMT in a combined study of men and women in Germany.10 However, our results differed. Measurements of PWV and IMT assess different aspects of the atherosclerotic process; vascular stiffness, being a dynamic property based on both vascular function and structure, can be quantified by PWV measurements, while more advanced structural vascular wall changes can be quantified by measuring IMT using B-mode ultrasound techniques.23 The difference in the stages that PWV and IMT focus on, may explain why our results differ from those of Wolff. In addition, while Wolff's subjects were people aged 45-81 years, living in the north-east coastal region of Germany, ours were Japanese public servants aged 35-60 years. Because our subjects were younger and healthier than Wolff's, our results may differ.
A systematic review of the associations between sleep duration and either all-cause of or cause-specific mortality indicated that long sleepers were at increased risk of cardiovascular-related mortality, but short sleepers were not.12 Results of a Japanese population study showed a U-shaped relationship between sleep duration and total mortality.24 However, cause-specific analyses indicated that long sleep duration was significantly associated with increased mortality from total cardiovascular disease in both sexes, while short sleep duration was not.11 Our results also revealed that long sleep duration (' 9 h) was only associated with elevated PWV as a marker of arterial stiffness. In non-western populations, epidemiological research on the effect of daily sleep duration and cardiovascular diseases is insufficient. Further studies are needed to clarify the effect of sleep duration on cardiovascular diseases in Asian countries.
The mechanisms underlying the associations between daily sleep duration and cardiovascular diseases are not fully understood. A number of experimental studies have shown that short sleep duration causes potentially adverse endocrinologic, immunologic, and metabolic effects.25,26 However, less attention has been directed at the health consequences of long sleep, although the body of research suggests that long sleep is more strongly associated with mortality than short sleep.12,27 A number of mechanisms for the association between long sleep and mortality were hypothesized in a recent review by Grandner and Drummond.27 These include (1) sleep fragmentation, (2) fatigue, (3) immune function, (4) photoperiodic abnormalities, (5) lack of challenge, (6) depression, or (7) underlying disease process such as (a) sleep apnea, (b) heart disease, or (c) failing health. Our results show that daily sleep duration of 9 hours or more was associated with higher PWV, being male, older age, higher systolic blood pressure, taking medication for hypertension. and more frequent alcohol consumption. Previous studies have indicated that these factors are also risk factors for sleep apnea,28–31 and that sleep apnea could cause elevated PWV.32–43 While high BMI (obesity), a known risk factor for sleep apnea,29– was not significantly associated with sleep duration, sleep apnea might explain the observed association between longer sleep duration and increased PWV in our research. Further studies are needed to clarify the mechanisms of sleep duration on the progression of atherosclerosis and cardiovascular disease.
Some limitations of this study need to be addressed. First, because our study is a cross-sectional study, the causal nature of the association between sleep duration and elevated PWV cannot be determined. Second, because the response rate in our study was rather low, our subjects might not necessarily be representative of the general group of civil servants in Japan. One previous report indicated that the daily average sleep duration of Japanese workers was 7 hours on weekdays.44 The average sleep duration of our subjects was 6.7 hours/day and thus comparatively shorter. This may mean that we underestimated the influence of long sleep on baPWV. In addition, the number of female subjects was much smaller than that of males. Consequently, there was a statistically significant association between sleep duration and elevated PWV among male subjects only. Third, information on sleep duration was obtained through self-reporting and can therefore be subject to error. Such errors, though, are equally likely for all study groups and may thus, given the size of our sample, have become negligible by chance. In addition, we did not obtain information about the quality of sleep, the presence of naps, and daily sleep duration on weekdays and weekends. Quality of sleep, such as the presence or absence of sleep apnea, is associated with increased risk of cardiovascular disease and arterial stiffness.32–43,45,46 Previous studies reported that napping was associated with nighttime sleep and cardiovascular outcomes.47–52 According to the “National Time Use Survey 2005 Report” from NHK Broadcasting Culture Research Institute,44 daily average sleep duration of Japanese workers was 7 hours on weekdays, 7.5 hours on Saturdays, and 8 hours on Sundays; thus the difference between weekdays and weekends might influence the results of our study. Fourth, we did not ask about the use of medications that could influence baPWV, such as vasoactive or anti-inflammatory drugs. We only obtained information on medication for hypertension, hyperlipidemia, and diabetes as a putative confounding factor, and significant association between long sleep duration and increased PWV was maintained after adjustment for them. In this article, data on medication for hyperlipidemia and diabetes were not shown. Finally, the relative small sample size of participants with self-reported sleep duration of 5 hours or less may explain the lack of increased arterial stiffness and short sleep duration in this subgroup.
In conclusion, daily sleep duration of 9 hours or more was associated with elevated values of baPWV as a marker of arterial stiffness. This suggests that there is an association between long sleep duration and arterial stiffness. Since regulating daily hours of sleep may contribute to a reduction in the incidence of cardiovascular diseases, further research is needed to examine the effect of daily sleep duration on cardiovascular disease.
DISCLOSURE STATEMENT
This was not an industry supported study. The authors have indicated no financial conflicts of interest.
ACKNOWLEDGMENTS
The authors thank Mr. Manabu Shojiguchi, Mr. Hiroyuki Arizuka, Ms. Toyoko Enomoto, Mr. Takanori Mogi, Mr. Naoto Sasaki, Mr. Takeshi Tsuda, Ms. Tomoko Arihara, Dr. Toshiyuki Hayashi, Ms. Chizuko Sato, and Dr. Takehito Naka-bayashi for their excellent assistance with data collection; and Ms. Akemi Onodera, Ms. Maki Fukushima, and Ms. Aki Yasuike for their assistance with the baPWV measurement. This work was supported in part by a Grant-in-Aid for Young Scientists from the Ministry of Education, Culture, Sports, Science and Technology of Japan and a Grant-in-Aid for Scientific Research from the Ministry of Health, Labour and Welfare of Japan.
Footnotes
A commentary on this article appears in this issue on page 1623.
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