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Journal of Public Health Advance Access originally published online on November 14, 2005
Journal of Public Health 2006 28(1):63-70; doi:10.1093/pubmed/fdi067
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© The Author 2006, Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved.

Explaining social inequalities in health by sleep: the Japanese civil servants study



Michikazu Sekine
Michikazu Sekine, MD PhD, MSc, Senior Lecturer, Department of Welfare Promotion and Epidemiology, University of Toyama, 2630 Sugitani Toyama 930-0194, Japan
Michikazu Sekine, MD PhD, MSc, Senior Lecturer, Department of Epidemiology and Public Health, University College London, 1-19 Torrington Place, London WC1E 6BT, UK


Tarani Chandola
Tarani Chandola, DPhil, Senior Lecturer, Department of Epidemiology and Public Health, University College London, 1-19 Torrington Place, London WC1E 6BT, UK


Pekka Martikainen
Pekka Martikainen, PhD, Senior Research Fellow, Department of Epidemiology and Public Health, University College London, 1-19 Torrington Place, London WC1E 6BT, UK
Pekka Martikainen, PhD, Senior Research Fellow, Department of Sociology, Population Research Unit, University of Helsinki, PO Box 18, FIN-00014, Finland


David McGeoghegan
David McGeoghegan, MSc, Senior Statistican, Westlakes Research Institute, The International Research and Graduate Centre, Westlakes Science and Technology Park, Moor Row, Cumbria CA24 3JY, UK


Michael Marmot
Michael Marmot, MD, PhD, Professor, Department of Epidemiology and Public Health, University College London, 1-19 Torrington Place, London WC1E 6BT, UK


Sadanobu Kagamimori
Sadanobu Kagamimori, MD, PhD, Professor, Department of Welfare Promotion and Epidemiology, University of Toyama, 2630 Sugitani Toyama 930-0194, Japan

Address correspondence to Michikazu Sekine. Email: sekine{at}ms.toyama-mpu.ac.jp

Background Individuals of low socioeconomic status (SES) are likely to have poor sleep and poor health. This study aims to evaluate whether and how much of the socioeconomic differences in health are explained by sleep.

Methods The subjects were 3684 (2471 males and 1213 females) employees aged 20–65 working in local government in Japan. A questionnaire survey was conducted in January 2003. Analysis of covariance (ANCOVA) was performed to examine the association of employment–grade with sleep, measured by the Pittsburgh Sleep Quality Index (PSQI), and with health, measured by the Physical and Mental Component Summary Scales (PCS and MCS) of the Short Form-36 (SF-36).

Results In men, higher grade employees had better sleep and better health. The age-adjusted difference between the highest and the lowest grade employees was 1.9 points (95% confidence interval = 1.0–3.0) in the PCS and 3.4 points (1.8–4.9) in the MCS. The grade difference in health reduced to 1.5 points (0.5–2.5) in the PCS (21.1% reduction) and 2.0 points (0.6–3.4) in the MCS (41.2% reduction), when the PSQI global score was adjusted for. The grade differences in sleep quality contributed more to the health inequalities than sleep quantity. Among women, no significant grade differences were observed in the PSQI global score. The grade differences in the PCS and MCS were weaker and less consistent than those of men, and the differences hardly changed when the PSQI global score was adjusted for.

Conclusion Sleep quality may mediate the relationship between SES and physical and, in particular, mental health in men.

Keywords: SF-36, PSQI, SES


   Introduction
TOP
 Introduction
Methods
 Results
 Discussion
 Conclusions
 Appendix: Pittsburgh Sleep...
 Acknowledgements
 References
 
Social inequalities in mortality rates have widened in several European countries in the last couple of decades, despite overall reductions in mortality rates.1,2 Although the established coronary risk factors (cigarette smoking, hypertension and hypercholesterolemia) are more common in lower socioeconomic status (SES) groups, these differences explained no more than one-third of the mortality difference among SES groups in the first Whitehall study.3 In addition, the international MONICA studies indicated that the international variations in the three established coronary risk factors accounted for less than half of the international variations in coronary heart disease mortality rates.4 As a consequence, other potential risk factors explaining social inequalities in health, including psychosocial stress at work and deprivation in early life, have been widely investigated.5,6

Sleep complaints are a common symptom in the general adult population and have been frequently observed in lower SES individuals.7–9 White-collar workers report better sleep than blue-collar workers, in terms of the difficulty in falling asleep, waking up frequently in the night and early morning awakening.7 Individuals from disadvantaged social classes are more likely to have sleep disturbances.8 During periods of severe economic recession in Finland, blue-collar workers were more likely to suffer from sleep problems than white-collar workers.9

Poor sleep quantity (i.e. short sleep duration) has been linked with mortality.10 In addition to the effect of short sleep duration on mental health deterioration,11,12 recent epidemiological and laboratory studies have shown that short sleep duration may also affect immune system dysfunction,13,14 obesity,15,16 diabetes,17 hypertension,17 coronary heart disease18,19 and stroke.19 Although there have been relatively fewer studies on the impact of poor sleep quality (i.e. the difficulty in falling asleep, waking up frequently in the night and early morning awakening) on health, significant associations of sleep quality with physical and mental health have been observed.20–22 In addition, there is some evidence that sleep quality has a stronger impact on health than sleep quantity.21

Because sleep is poorer among the lower SES groups, differences in sleep among different SES groups may affect social inequalities in physical and mental health. However, few studies have addressed this issue.22 Moore et al.22 reported that (i) the relationship between SES and physical and mental health was mediated by sleep quality and (ii) although sleep quantity was associated with both physical and mental health, sleep quantity was not associated with SES in a community sample of about 1000 adults. We are currently conducting an epidemiological study on approximately 4000 Japanese civil servants.23,24 The study allows us to evaluate each role for quality and quantity aspects of sleep in the relationship between SES and health with considerable advantages in terms of subject number and the use of valid and reliable questionnaires for sleep and health.

The purpose of this study is, therefore, to clarify the following research questions in a population of Japanese civil servants: whether social inequalities in sleep explain, in part, social inequalities in health; which aspects of sleep contribute to social inequalities in health; and finally how much of the social inequalities in health are explained by sleep.


   Methods
TOP
 Introduction
 Methods
Results
 Discussion
 Conclusions
 Appendix: Pittsburgh Sleep...
 Acknowledgements
 References
 
Subjects
The Japanese civil servants study is an international collaborative study with the British civil servants study.23,24 The subjects of this study were civil servants in local government in Japan. The subjects mainly consisted of clerical workers, professional and technical workers (technician, teachers and hospital workers), and office support staff (protection workers, telecommunication workers and transportation workers). An ad hoc committee of the civil service approved the content and ethical aspects of this study. A questionnaire was distributed and gathered through the personnel section of the local government department between January and February 2003. The subjects gave informed consent and participated voluntarily in this study. Altogether, 4272 subjects (response rate 79.2%) responded to the questionnaire. Subjects who did not answer one or more questions about age, sex, grade of employment, sleep and physical and mental health (588 subjects) were excluded in the analysis. The remaining 3684 subjects (2471 men and 1213 women) represented the study population. The mean age of the subjects was 42.8 years (standard deviation 10.3).

Measures for physical and mental health
The Short Form 36 (SF-36) was used to measure physical and mental health function of the civil servants. The original questionnaire has been used worldwide.25,26 A Japanese version of the SF-36 has been validated and widely used in Japan.27–29 In the SF-36, one item is designed to assess perceived change in health status, and the remaining 35 items are used to generate eight subscales (0–100 scale): physical functioning (PF); role limitations due to poor physical health (RP); bodily pain (BP); general health perception (GH); vitality (VT); social functioning (SF); role limitations due to poor emotional health (RE) and mental health (MH). The subscale scores were standardized by using the general US population to generate a corresponding z-score. Aggregate physical and mental component summary scores of the SF36 (PCS and MCS, respectively) were obtained by multiplying each z-score by its respective physical and mental factor score coefficient and summing these eight products. Finally, each aggregate component score was transformed to a norm-based score with a US population mean of 50 and standard deviation of 10. The higher scores represent better health. Cronbach’s alpha for the Japanese version ranged from 0.71 to 0.91,29 and the test–retest reliability ranged from 0.78 to 0.86 implying reasonably good validity and reliability for the Japanese version.29

Measures for sleep quality and quantity
The Pittsburgh Sleep Quality Index (PSQI) was used to measure sleep quality and quantity in the previous month (see Appendix). The PSQI is a self-rated questionnaire consisting of 17 items.30 A Japanese version of the questionnaire has been developed31 and was used in this study. The items were used to generate seven components: subjective sleep quality; sleep latency; sleep duration; habitual sleep efficiency; sleep disturbance; use of sleep medication and daytime dysfunction. Each component score has a range of 0–3. The sum of these seven component scores provides a global PSQI score, which has a range of 0–21. Higher scores equate to poorer sleep. This questionnaire has been extensively used to investigate the sleep quality and quantity of non-clinical populations20,32 and psychiatric patients.30,33 A cut-off score of more than 5.5 has a sensitivity of 80.0–85.7% for various patients groups and a specificity of 86.6% for control subjects in the Japanese version of the PSQI.33 The overall reliability coefficient was high (Cronbach’s {alpha}34 = 0.77)33.

Measure for SES
Grades of employment have often been used as a measure of SES of employed men and women.24,35 We, therefore, used grades of employment as a measure of SES in this study. Grades of employment were based on questionnaire information and ranked hierarchically in the following way: senior administrative workers (highest grade employees) with an employment grade of section leader or higher (e.g. Head of Bureau, Head of Department, Deputy Head of Department and Head of Section) and professional equivalents; administrative workers (intermediate grade employees) with an employment grade of lower than section leader (e.g. Assistant Head of Section and Subsection Chief) and professional equivalents; civil servants with no administrative title (lowest grade employees) and professional equivalents.

Although one of the major characteristics of payment systems in Japanese organizations is seniority-based wages,36 a previous study showed that employment grade was the largest contributor to earnings and accounted for on average 40% of earnings in employees of a Japanese firm.37

Statistical analysis
To evaluate the possible non-response biases in this study, the difference in age, sex and grades of employment between the study subjects and those excluded were compared by using the unpaired t-test for continuous variables (i.e. age) and the {chi}2 test for categorical variables (i.e. sex and grades of employment). The differences in personal attributes between the study subjects and those excluded indicated that those excluded tended to be older and female, although there were no significant differences by grade of employment.

To examine whether there were employment–grade differences in the mean scores of the SF-36 and PSQI, analysis of covariance (ANCOVA) was performed separately by sex, using age as the covariate. Also, the contribution of grade differences in sleep to inequalities in physical and mental health was examined by ANCOVA using age and one of the PSQI scales as covariates. Bonferroni’s test was used to test the difference in the scores between any two of the three SES groups. Mean score differences in the health measures between the highest and the lowest grade employees were calculated to quantify the magnitude of the grade difference in health.

Statistical analyses were performed using SPSS software (10.0J).38 A two-tailed p-value of less than 0.05 was considered to be statistically significant.


   Results
TOP
 Introduction
 Methods
 Results
Discussion
 Conclusions
 Appendix: Pittsburgh Sleep...
 Acknowledgements
 References
 
Table 1 summarizes the characteristics of the study subjects. Men were significantly older than women. In comparison with men, the proportion of the highest grade employees among women was very small. Men had better sleep and better physical and mental health than women. The reliability coefficients (Cronbach’s alphas) of the subscales and two summary scales of the SF-36 ranged from 0.76 to 0.88, whereas the overall reliability coefficient of the PSQI was 0.63, indicating that both instruments had acceptable reliability for a comparison of the score differences of the groups.39


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  		Table 1 Characteristics of the study subjects

 

Table 2 summarizes the age-adjusted grade differences in the PSQI scales. In men, there were significant employment–grade differences in all PSQI scales other than for sleep duration and daytime dysfunction. The highest grade employees showed the lowest score (best for sleep), followed by the intermediate grade employees and the lowest grade employees. In women, no significant grade differences in sleep measures were observed. In addition, the relationship between grades of employment and sleep was less consistent in women than men. In men, the prevalence of poor sleep quality (PSQI > 5.5) was 15.1% for the highest grade employees, 20.0% for the intermediate grade employees and 23.4% for the lowest grade employees. In women, the prevalence of poor sleep quality was 25.0% for the highest grade employees, 34.8% for the intermediate grade employees and 31.2% for the lowest grade employees.


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  		Table 2 Adjusted grade differences in the Pittsburgh Sleep Quality Index (PSQI) of Japanese civil servants

 

Table 3 summarizes unadjusted and adjusted grade differences in the PCS. In men, the highest grade employees had the healthiest PCS, followed by the intermediate grade and the lowest grade employees but only for adjusted difference. The age-adjusted difference in the score between the highest grade and lowest grade employees was 1.9 points (95% confidence interval = 1.0–3.0). Although the difference reduced somewhat after adjustment for one of the PSQI scales (particularly for subjective sleep quality, sleep latency and sleep disturbances), the most prominent reduction was observed when the global score was adjusted for [the difference was 1.5 points (0.5–2.5)] (21.1% reduction). In women, the pattern of grade difference was different from men. The difference hardly changed after adjustment for any one of the PSQI scales.


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  		Table 3 Unadjusted and adjusted grade differences in the Physical Component Summary Scale (PCS) of Japanese civil servants

 

Table 4 summarizes unadjusted and adjusted employment grade differences in the MCS. In men, the highest grade employees had the healthiest MCS scores, followed by the intermediate grade employees and then the lowest grade employees. The age-adjusted mean difference of the MCS between the highest and the lowest grade employees was 3.4 points (1.8–4.9). Although the difference reduced somewhat after adjustment for any one of the PSQI scales (particularly subjective sleep quality, sleep latency and sleep disturbances), the most prominent reduction was observed when the global score was adjusted for [the difference was 2.0 points (0.6–3.4)] (41.2% reduction). In women, no statistically significant grade differences in the MCS were observed, and the differences hardly changed after adjustment for any one of the PSQI scales.


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  		Table 4 Unadjusted and adjusted grade differences in the Mental Component Summary Scale (MCS) of Japanese civil servants

 


   Discussion
TOP
 Introduction
 Methods
 Results
 Discussion
Conclusions
 Appendix: Pittsburgh Sleep...
 Acknowledgements
 References
 
Main findings
In men, social inequalities in sleep, physical and mental health existed. Higher grade employees had better sleep and better physical and mental health. In addition, the differences between high and low employment grades in physical and mental health reduced by approximately 20 and 40%, respectively after adjustment for the differences in sleep. These results suggest that social inequalities in sleep could influence, in part, social inequalities in physical and, in particular, mental health. Furthermore, among various aspects of sleep, quality aspects of sleep (i.e. subjective sleep quality, sleep latency and sleep disturbances) contributed more to the reduction in social inequalities in health than quantity aspects of sleep (i.e. sleep duration).

In women, there were no significant grade differences in sleep. Furthermore, the differences in physical and mental health were weaker and less consistent than those of men, and these hardly changed after adjustment for any one of the PSQI scales.

What is already known on this topic
The prevalence of poor sleep is reported to be higher among low SES individuals than among high SES individuals.7–9 Akerstedt et al.40 reported that a poor work environment including low job control, high demand and low social support at work were related to disturbed sleep. Because such work characteristics are commonly observed in low SES groups,35 low SES individuals may be more likely to suffer from poor sleep.

Socioeconomic differences in physical health are well known. Martikainen et al.24 reported socioeconomic inequalities of ill health and physical functioning among men and women in Britain and Finland, and among men in Japan. In addition, although the pattern of socioeconomic difference of ill health among British and Finnish women were quite similar to that of men in the same countries (i.e. the lower the SES, the poorer the health), the SES pattern among Japanese was less consistent in women than men. This study data are consistent with those findings. Although the reason for the different pattern of socioeconomic differences of ill health among Japanese versus British and Finnish women is not necessarily clear, different patterns of female labour force participation and differences in female occupations between these countries may contribute. Furthermore, there is some evidence that the association between health and SES among women is not as strong when they are classified by their own occupation rather than their head of household’s occupation.41 It is possible that household SES differences in health and sleep among Japanese women may resemble the male pattern, but such data were not collected in this study. In addition, because the number of highest grade employees among women was very small, the results pertaining to the pattern of grade difference in women should be treated cautiously.

In this study, mean scores of sleep and mental health measures were much lower and poorer among women than men. Doi et al.32 also reported that the prevalence of poor sleep quality was 31.1% for women and 26.4% for men in the general Japanese adult population. Lahelma et al.42 reported that women were more likely to report mental and somatic symptoms than men in Finland. The reason for the sex difference in sleep quality and health status is not clear, but biological factors, health behaviours and reporting differences have been suggested as possible causes.42,43

What this study adds
Moore et al.22 reported that sleep quality played a mediating role in translating SES into physical and mental health, and there was no significant SES difference in sleep quantity. In this study, we have confirmed the above findings but only for men. Thus, we found that there was a gender difference for the role of sleep in the relationship between SES and health. The gender difference is at least partly due to the fact that there were no significant SES differences in sleep among women. We also found that among the various aspects of sleep the overall sleep measure and, to a lesser degree, quality aspects of sleep affected social inequalities in health, to greater extent, than quantity aspects of sleep. In addition, the SES difference in sleep contributed more to the SES difference in mental health than that for physical health. These results suggest that the mediating role of sleep in the relationship between SES and health may differ between men and women, between sleep quality and quantity, and between physical and mental health.

Methodological considerations
It should be mentioned there are several limitations in this study. Firstly, this study is a cross-sectional study which makes it impossible to determine causality for the relationship between grades of employment, sleep and health status.

Secondly, the questionnaire statements on sleep may conceptually overlap with those on physical and mental health. The PSQI global score was correlated weakly with the PCS (r = –0.28) and moderately with the MCS (r = –0.50), respectively. However, the PCS and MCS scores are designed to be orthogonal and uncorrelated with each other. So any correlation between sleep and PCS is unlikely to result from the correlation between sleep and MCS.

Thirdly, it may be difficult to generalize the findings from this study to the general Japanese population. The subjects of this study were working civil servants, who were relatively young, well-educated and white-collar in comparison to the general Japanese adult population. The study population did not include the extremes of SES. Thus, in the general population, the relationship of SES with SF-36 scores and the mediating effect of sleep on the relationship may be much stronger.


   Conclusions
TOP
 Introduction
 Methods
 Results
 Discussion
 Conclusions
Appendix: Pittsburgh Sleep...
 Acknowledgements
 References
 
Sleep quality may mediate the relationship between SES and physical and, in particular, mental health in Japanese men. Longitudinal research is necessary to determine the causality.


   Appendix: Pittsburgh Sleep Quality Index
TOP
 Introduction
 Methods
 Results
 Discussion
 Conclusions
 Appendix: Pittsburgh Sleep...
Acknowledgements
 References
 
The following questions relate to your usual sleep habits during the past month only. Your answers should indicate the most accurate reply for most of the days and nights in the past month. (In no. 1–5, subjects are asked to answer in hours and minutes. In no. 6–9, the subjects are asked to check the one best response.)


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   Acknowledgements
TOP
 Introduction
 Methods
 Results
 Discussion
 Conclusions
 Appendix: Pittsburgh Sleep...
 Acknowledgements
References
 
We are indebted to all the civil servants in the local government for their participation in this study and Ms. Yasuko Yamazaki for her clerical support. This study was in part granted by the Japanese Society for the Promotion of Science, the Occupational Health Promotion Foundation, the Univers Foundation, the Daiwa Anglo-Japanese Foundation (03/2059) and the Great Britain Sasakawa Foundation (2551). Funding organizations were not involved in the design, conduct, interpretation and analysis of the study, nor review or approval of the manuscript.

MS is supported by British Heart Foundation Travelling Fellowship (FS/04/051).

TC and MM are supported by grants from the Medical Research Council; British Heart Foundation; Economic and Social Research Council; Health and Safety Executive; Department of Health; National Heart Lung and Blood Institute (HL36310), US, NIH; National Institute on Aging (AG13196), US, NIH; Agency for Health Care Policy Research (HS06516) and the MacArthur Foundation.

PM is supported by a fellowship and a grant from the Academy of Finland (70631, 48600), and the Gyllenberg Foundation.

This paper was partly presented at the 48th Annual Scientific Meeting of Society for Social Medicine at Birmingham in September 2004.


   References
TOP
 Introduction
 Methods
 Results
 Discussion
 Conclusions
 Appendix: Pittsburgh Sleep...
 Acknowledgements
 References
 

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