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American Journal of Epidemiology Advance Access originally published online on November 15, 2007
American Journal of Epidemiology 2008 167(3):321-329; doi:10.1093/aje/kwm302
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American Journal of Epidemiology © The Author 2007. Published by the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.

ORIGINAL CONTRIBUTIONS

Cross-sectional versus Prospective Associations of Sleep Duration with Changes in Relative Weight and Body Fat Distribution

The Whitehall II Study

Saverio Stranges1, Francesco P. Cappuccio1, Ngianga-Bakwin Kandala1, Michelle A. Miller1, Frances M. Taggart1, Meena Kumari2, Jane E. Ferrie2, Martin J. Shipley2, Eric J. Brunner2 and Michael G. Marmot2

1 Cardiovascular Medicine and Epidemiology Group, Clinical Sciences Research Institute, University of Warwick Medical School, Coventry, England
2 International Centre for Health and Society, University College London Medical School, London, England

Correspondence to Professor Francesco P. Cappuccio, Cardiovascular Medicine and Epidemiology Group, Clinical Sciences Research Institute, University of Warwick Medical School, University Hospital Coventry and Warwickshire Campus, Clifford Bridge Road, Coventry CV2 2DX, England (e-mail: cvme{at}warwick.ac.uk).

Received for publication June 8, 2007. Accepted for publication September 20, 2007.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
A cross-sectional relation between short sleep and obesity has not been confirmed prospectively. The authors examined the relation between sleep duration and changes in body mass index and waist circumference using the Whitehall II Study, a prospective cohort of 10,308 white-collar British civil servants aged 35–55 years in 1985–1988. Data were gathered in 1997–1999 and 2003–2004. Sleep duration and other covariates were assessed. Changes in body mass index and waist circumference were assessed between the two phases. The incidence of obesity (body mass index: ≥30 kg/m2) was assessed among nonobese participants at baseline. In cross-sectional analyses (n = 5,021), there were significant, inverse associations (p < 0.001) between duration of sleep and both body mass index and waist circumference. Compared with 7 hours of sleep, a short duration of sleep (≤5 hours) was associated with higher body mass index (β = 0.82 units, 95% confidence interval (CI): 0.38, 1.26) and waist circumference (β = 1.88 cm, 95% CI: 0.64, 3.12), as well as an increased risk of obesity (odds ratioadjusted = 1.65, 95% CI: 1.22, 2.24). In prospective analyses, a short duration of sleep was not associated with significant changes in body mass index (β = –0.06, 95% CI: –0.26, 0.14) or waist circumference (β = 0.44, 95% CI: –0.23, 1.12), nor with the incidence of obesity (odds ratioadjusted = 1.05, 95% CI: 0.60, 1.82). There is no temporal relation between short duration of sleep and future changes in measures of body weight and central adiposity.

body fat distribution; body weight changes; obesity; sleep

Abbreviations: BMI, body mass index; CI, confidence interval; OR, odds ratio


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
Numerous epidemiologic studies indicate possible associations between sleep disturbances or voluntary shortened sleep duration and several health outcomes, including total mortality, cardiovascular disease, type 2 diabetes mellitus, respiratory disorders, and poor self-rated health (1–13). In addition, several studies have suggested a relation between short sleep duration and increased body weight or obesity in both children and adults (14–26). Specifically, an inverse association has been reported between the number of hours of sleep and body weight or body mass index. However, these observations come predominantly from cross-sectional studies (14–22). Results from a few longitudinal analyses have been inconsistent, with only one study showing significant, consistent associations (23–26). Specifically, a recently published report from the Nurses' Health Study has shown that a habitual sleep time of less than 7 hours predicted a modest increase in weight and incident obesity independent of baseline weight (26). This analysis, however, was based on self-reported measures of body weight, was limited to a large cohort of highly selected middle-aged women, and did not take measures of body fat distribution into account. Altogether, the current epidemiologic evidence does not allow for conclusive inferences in favor of a causal link between short sleep duration and obesity because of a number of unresolved issues (27, 28). First, sleep disorders are often comorbid, especially in the elderly, with medical and psychiatric conditions that can compromise the quality and duration of sleep (29), thus increasing the likelihood of reverse causality and bidirectional relations, especially in cross-sectional studies. Second, the biologic mechanisms underlying the observed associations are unclear, although the evidence from experimental studies suggests possible explanations, such as alterations in hormonal and neurovegetative responses, and effects on the immune function. Third, given the lack of specificity of the observed associations, it is possible that other factors or comorbid conditions may confound the associations between duration and quality of sleep and health outcomes.

The Whitehall II Study gives a unique opportunity to address several of the open questions discussed above. Specifically, in this study, we sought to examine the cross-sectional and longitudinal relations between sleep duration and changes in continuous measures of relative weight (i.e., body mass index (BMI)) and body fat distribution (i.e., waist circumference), as well as the incidence of obesity and overweight, taking into account a number of potential confounding factors.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 References
 
Study population
The Whitehall II cohort was recruited in 1985–1988 (phase 1) from 20 London-based Civil Service departments. The rationale, design, and methods of the study have been described in detail elsewhere (30). Briefly, the study was set up to determine the pathways underlying the social differences in health that were apparent in the original Whitehall Study (31), and it was specifically designed to focus on pathways not originally examined, such as psychosocial and dietary factors. The initial response rate was 73 percent, and the final cohort consisted of 10,308 participants: 3,413 women and 6,895 men. Follow-up screening examinations took place in 1991–1993 (phase 3), 1997–1999 (phase 5), and 2003–2004 (phase 7), whereas postal questionnaires were sent to participants in 1989 (phase 2), 1995 (phase 4), and 2001 (phase 6). The participation rates of the original cohort (n = 10,308) were 83 percent, 76 percent, and 68 percent at phases 3, 5, and 7, respectively. In this report, we used data from phase 5 and phase 7. The total sample at phase 5 consisted of 7,204 participants, after excluding those who did not provide complete data (n = 630). The present analyses were restricted to White individuals (n = 6,592), given the low numbers of other ethnic groups (n = 612). For the cross-sectional analyses, only participants with a complete set of data at phase 5 were included (n = 5,021). For the longitudinal analyses on changes in continuous measures of body mass index and waist circumference between phases 5 and 7, only participants with a complete set of data at both phases were included (n = 4,378). Finally, the incidence of obesity (BMI: ≥30 kg/m2) at phase 7 was assessed among nonobese participants at phase 5 (n = 3,786). For the purpose of sensitivity analysis, the combined incidence of overweight and obesity (BMI: ≥25 kg/m2) at phase 7 was also assessed among normal-weight participants at phase 5 (n = 1,887).

Sleep duration
At phases 5 and 7, sleep duration was elicited by the question, "How many hours of sleep do you have on an average week night?" Response categories were 5 hours or less, 6, 7, 8, and 9 hours or more.

Covariates
For the present analyses, age and other covariates were derived from the questionnaire at phase 5. Employment grade, as a measure of current or recent social position, was determined from the participants' last known Civil Service grade title (19 percent had retired by phase 5) and divided into three categories in order of decreasing salary: professional/executive, administrative, and clerical/support. Participants were allocated to one of four smoking categories: never, former smoker, pipe and/or cigar only, or current cigarette smoker (manufactured or hand-rolled cigarettes). Alcohol consumption in the previous week was recorded (units per week). For leisure-time physical activity, participants were asked to indicate the number of occasions and hours spent doing a series of specific activities over the past 4 weeks. These activities were classified into light, moderate, or vigorous activities on the basis of their energy expenditure (metabolic equivalents). In this study, leisure-time physical activity was categorized by energy use in two categories: "vigorous" (subjects who reported at least 1.5 hour of vigorous activity per week) and no vigorous activity. General health status was assessed by use of the physical and mental health component summaries of the Short Form-36 health survey questionnaire (32); low scores indicate low functioning. Psychiatric morbidity including depressive symptoms was assessed with a modified General Health Questionnaire score. Participants taking sleep medication (hypnotics) or cardiovascular drugs were identified through a questionnaire item on current medication. Specifically, participants listed all medications that had been prescribed by a physician that they had taken in the last 14 days. These medications were coded to classify types of medications. Medication for cardiovascular disease included any antihypertensive drugs, lipid-lowering drugs, nitrates, or antiplatelet drugs. At the screening examinations for both phase 5 and phase 7, several anthropometric measures were recorded, including height, weight, and waist circumference; body mass index was calculated (weight (kg)/height (m)2).

Ethical approval
Ethical approval for the Whitehall II Study was obtained from the University College London Medical School committee on the ethics of human research.

Statistical analysis
For continuous and categorical variables, respectively, Kruskal-Wallis and {chi}2 tests were used to determine the statistical significance of any difference in the distribution of baseline variables at phase 5 across categories of sleep duration. Multivariate linear regression analyses were performed to test the association between categories of sleep duration and continuous measures of body mass index and waist circumference at phase 5 (cross-sectional analyses), as well as the association between categories of sleep duration at phase 5 and changes in body mass index and waist circumference between the two phases (prospective analyses), by modeling four dummy variables and using 7 hours of sleep as the reference category. The coefficients estimate the adjusted mean difference in body mass index and waist circumference or changes in body mass index and waist circumference between each category and the reference category. Covariates included the following: baseline age, sex, and employment, as well as the baseline value of body mass index or waist in prospective analyses to account for the phenomenon of "regression to the mean" (33) (model 1); alcohol consumption, smoking, physical activity, and cardiovascular disease drugs (model 2 + the variables of model 1); and the Short Form-36 mental and physical health scores, depressive symptoms, and use of hypnotics (model 3 + the variables of model 2). Logistic regression analyses were also performed to examine the cross-sectional association between categories of sleep duration and prevalent obesity (BMI: ≥30) at phase 5, as well as the prospective association between categories of sleep duration at phase 5 and incident obesity at phase 7 among participants who were nonobese (BMI: <30) at phase 5. Sensitivity analyses were performed by use of the cutoff value for overweight (BMI: ≥25) to assess the prevalence, as well as the incidence, of combined overweight and obesity. In these analyses, the duration of 7 hours of sleep was selected as the reference category. Subgroup analyses were also performed after exclusion of participants on medication for cardiovascular disease. All analyses were carried out using STATA, version 9.0, software (StataCorp LP, College Station, Texas).


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 References
 
Characteristics of participants at phase 5 ("baseline") are reported in table 1 by categories of sleep duration and sex. In general, participants of both sexes sleeping 5 hours or less had a poorer health status and lifestyle profile. For example, they had higher mean levels of body mass index and waist circumference, were less likely to be physically active, and were more likely to be current smokers (men only); they were more likely to use cardiovascular disease drugs (women only), were more likely to report depressive symptoms, and had lower scores for mental and physical health than other categories.


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  		TABLE 1. Baseline characteristics* of subjects by sleep duration category and by sex at phase 5 (1997–1999), the Whitehall II Study, London, England (n = 5,021)

 
Table 2 shows the cross-sectional association between categories of sleep duration and continuous measures of body mass index and waist circumference at phase 5. Compared with participants sleeping 7 hours, those sleeping 5 hours or less were characterized by higher levels of both body mass index (β = 0.82 units, 95 percent confidence interval (CI): 0.38, 1.26) and waist circumference (β = 1.88 cm, 95 percent CI: 0.64, 3.12). Moreover, there were consistent, significant inverse associations (p < 0.001) between duration of sleep (as a continuous variable) and both body mass index (β = –0.36, 95 percent CI: –0.49, –0.24) and waist circumference (β = –0.96, 95 percent CI: –1.32, –0.60) (Web Appendix 1). (This information is described in the first of four supplementary appendixes; each is referred to as "Web Appendix" in the text and is posted on the Journal's website (http://aje.oxfordjournals.org/).)


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  		TABLE 2. Cross-sectional relations* of duration of sleep (hours) with body mass index and waist circumference at phase 5 (1997–1999), the Whitehall II Study, London, England (n = 5,021)

 
Table 3 shows the prospective association between categories of sleep duration at phase 5 and changes in body mass index and waist circumference between the two phases. Compared with 7 hours of sleep, a short duration of sleep (i.e., ≤5 hours) was not associated with significant changes in body mass index (β = –0.06, 95 percent CI: –0.26, 0.14) or waist circumference (β = 0.44, 95 percent CI: –0.23, 1.12). Results were virtually identical without the inclusion of the baseline value of body mass index (β = –0.06, 95 percent CI: –0.25, 0.14) or waist circumference (β = 0.37, 95 percent CI: –0.31, 1.05). When using duration of sleep as a continuous variable, we observed no significant changes in body mass index (β = 0.03, 95 percent CI: –0.03, 0.08) or waist circumference (β = –0.08, 95 percent CI: –0.28, 0.11) between the two phases. Findings were not substantially changed after exclusion of participants taking cardiovascular disease drugs (n = 639) (Web Appendix 2 and Web Appendix 3).


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  		TABLE 3. Prospective relations* of duration of sleep (hours) with changes in body mass index and waist circumference between phase 5 (1997–1999) and phase 7 (2003–2004), the Whitehall II Study, London, England (n = 4,378)

 
Table 4 displays the odds ratios of prevalent obesity (n = 691, 13.8 percent) across categories of sleep duration at phase 5, with 7 hours of sleep as the reference category. In the fully adjusted model, participants sleeping 5 hours or less had a significant increased risk of obesity (odds ratio (OR) = 1.65, 95 percent CI: 1.22, 2.24) compared with those sleeping 7 hours, with a significant liner trend across categories of sleep duration (p = 0.003). Likewise, in sensitivity analyses, participants sleeping 5 hours or less reported a significant increased combined prevalence of overweight and obesity (OR = 1.41, 95 percent CI: 1.10, 1.80) compared with those sleeping 7 hours, with a significant linear trend across categories of sleep duration (p < 0.001).


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  		TABLE 4. Odds ratios of prevalent obesity and overweight plus obesity across categories of sleep duration at phase 5 (1997–1999), the Whitehall II Study, London, England (n = 5,021)

 
Table 5 displays the odds ratios of incident obesity (n = 246, 6.5 percent) at phase 7 among participants who were nonobese (BMI: <30) at phase 5 (n = 3,786). No significant associations were reported across categories of sleep duration, although the risk estimates of obesity were in the expected direction among participants sleeping less than 7 hours (for 6 hours: OR = 1.21, 95 percent CI: 0.89, 1.64; for ≤5 hours: OR = 1.05, 95 percent CI: 0.60, 1.82). Likewise, no significant associations were reported when using a different cutoff value (BMI: ≥25 kg/m2) for the combined incidence of overweight and obesity (for 6 hours: OR = 1.09, 95 percent CI: 0.83, 1.41; for ≤5 hours: OR = 1.28, 95 percent CI: 0.80, 2.06). After exclusion of participants on cardiovascular disease drugs, findings were not substantially different (Web Appendix 4).


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  		TABLE 5. Odds ratios of incident obesity (n = 3,786)* and incident overweight plus obesity (n = 1,887){dagger} at phase 7 (2003–2004) across categories of sleep duration at phase 5 (1997–1999), the Whitehall II Study, London, England

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
References
 
Cross-sectional findings from the Whitehall II cohort showed that a shorter duration of sleep was significantly associated, in a linear fashion, with greater body weight and risk of obesity, which is consistent with previous cross-sectional reports (14–22, 24). Specifically, the regression coefficient of –0.36 (95 percent CI: –0.49, –0.24) for the cross-sectional association between the number of hours of sleep and body mass index is consistent with the magnitude of the association observed in a recently published cross-sectional analysis from a population-based sample in the United States (21). Moreover, unlike previous investigations, which did not include measures of body fat distribution and central adiposity, in the cross-sectional analyses we also found a significant, inverse association between hours of sleep and waist circumference. Finally, individuals sleeping 5 hours or less had a 65 percent increased risk of obesity compared with those sleeping 7 hours, in fully adjusted models, which is consistent with pooled estimates reported in a meta-analysis of cross-sectional studies (34).

The prospective analyses, however, did not show a significant association between sleep duration and future changes in body weight or waist circumference, therefore not supporting a temporal relation between short sleep duration and obesity, an essential criterion to infer causality. Indeed, most of the evidence so far comes from cross-sectional analyses (14–22, 24), which preclude the possibility of sorting out the bidirectional relation between sleep duration and body weight. On the other hand, change models offer the possibility of controlling for all time-stable confounders. Obesity is often comorbid with several medical conditions that in turn may impair the quality and duration of sleep (29). Findings from a few longitudinal investigations have been inconsistent (23–26). First, Hasler et al. (23) found that short sleep time was associated with subsequent obesity in subjects younger than 35 years, but the association diminished in older participants. However, this study was based on a small sample (n = 496) with overrepresentation of cases with psychiatric disorders and, thus, with a limited generalizability. In addition, in this study, the potential for reverse causality could not be excluded because the authors also found an association between earlier obesity and future short sleep duration. Second, Gangwisch et al. (24) reported inconsistent findings from cross-sectional and longitudinal analyses of the large US sample of the First National Health and Nutrition Examination Survey. Similar to our findings, those of Gangwisch et al. included significant cross-sectional associations between short sleep duration and high levels of body weight and obesity, whereas sleep duration at baseline was not associated with significant future changes in body mass index over a mean follow-up of 8–10 years (β = –0.053; p = 0.27), consistent with our findings. It should be noted, however, that this analysis was based on self-reported weights to compute body mass index during the follow-up and did not include measures of body fat distribution. Third, a recently published report from the large sample of the Nurses' Health Study (n = 68,183) has shown that a habitual sleep time of less than 7 hours predicted a modest increase in weight over a mean follow-up of 16 years (26). In addition, the relative risks for incident obesity were 1.15 (95 percent CI: 1.04, 1.26) and 1.06 (95 percent CI: 1.01, 1.11) for women sleeping 5 and 6 hours, respectively, compared with those sleeping 7 hours, which resemble our point risk estimates. However, this analysis was based on self-reported measures of body weight, did not include measures of body fat distribution, and was limited to a large cohort of middle-aged women from the nursing profession, thus with a limited generalizability. Conversely, there were no significant associations between sleep duration at baseline and weight gain (and incident type 2 diabetes) in a population-based study of 1,462 Swedish women followed for 32 years (25). It should be noted that, in this study, the authors did find significant, inverse associations between sleep duration and body mass index and waist/hip ratio in cross-sectional analyses at baseline, which is consistent with our findings. In summary, our results are consistent in showing inverse cross-sectional relations between short sleep and obesity but no prospective associations.

The biologic mechanisms underlying the observed associations between short sleep duration and increased body weight are unclear, although the evidence from physiologic studies suggests some possible explanations. For example, sleep deprivation has been found to influence hormones that control appetite. In a small study of 12 young, healthy men, an induced short-term sleep restriction was associated with a reduction in the levels of the anorexigenic hormone leptin on one hand and an increase in the levels of the orexigenic hormone ghrelin and, thus, increased hunger (35). Similar associations were found in cross-sectional analyses from the Wisconsin Sleep Cohort Study, suggesting that these effects may persist with long-term sleep restriction (19). Glucose homeostasis is also affected by sleep deprivation, because glucose uptake varies through different phases of sleep, and adverse effects of sleep deprivation have been reported on cortisol levels, glucose tolerance, and growth hormone secretion (36–38). Moreover, sleep deprivation has been associated with changes in levels of circulating catecholamines and alterations of neurovegetative responses (39). Recent findings also suggest that sleep may have powerful effects on the immune function and that inflammatory responses to sleep deprivation may represent one mechanism linking short sleep duration to obesity and other metabolic disorders (40–43). Finally, we cannot exclude that sleep deprivation may represent a risk marker for poorer health outcomes and impaired quality of life rather than a casual factor for obesity and other related diseases (11). Indeed, our descriptive analyses showing a poorer health status and lifestyle profile associated with shorter duration of sleep strongly suggest that other factors and comorbidities could confound the associations between duration and quality of sleep and health outcomes.

There are some limitations to our study. First, the population is an occupational cohort of white-collar workers and is limited to Whites, which may reduce the generalizability of our findings to other populations. However, this would not affect the internal validity of our results with respect to the longitudinal analyses. Second, information about sleep duration was self-reported by the participants. Nevertheless, self-report assessments of sleep have been shown to be valid measures compared with quantitative sleep assessments with actigraphy (44). Moreover, because outcomes were assessed prospectively, any misclassification of sleep duration would be nondifferential with respect to weight gain, thus resulting in underestimation of the true effects. A further limitation of this study is the relatively short time of follow-up (5 years), which may have precluded us from detecting larger and significant effects of sleep deprivation on future changes in body weight and fat distribution. However, other longitudinal analyses (23–25), but one (26), based on longer follow-ups, still failed to detect significant and consistent associations. The strengths of this study include the simultaneous inclusion of a number of covariates known to be related to both sleep habits and obesity. A further strength is that anthropometric measures of relative weight and body fat distribution were directly measured at both examinations and were not based on questionnaires as in previous longitudinal investigations, thus minimizing the potential of recall bias and misclassification that occur when using self-report alone.

In summary, consistent with previous investigations, this study demonstrates significant associations between short duration of sleep and greater body weight, central adiposity, and risk of obesity, in cross-sectional analyses. However, prospective analyses do not support a temporal relation between short duration of sleep and gains in body weight or central adiposity, which is consistent with all (23–25) but one (26) previous longitudinal studies. Although sustained sleep curtailment and ensuing excessive daytime sleepiness are undoubtedly cause for concern, our study suggests that short duration of sleep might represent a risk marker rather than a causative risk factor for obesity. Further prospective studies with objective assessment of long-term exposure (e.g., repeated actigraphy), more specific outcomes (including direct measures of adiposity), and better control for confounders are needed before causality can be determined.


   ACKNOWLEDGMENTS
 
The Whitehall II Study has been supported by grants from the Medical Research Council, the British Heart Foundation, the Health and Safety Executive, and the Department of Health; the National Heart, Lung, and Blood Institute (grant HL36310) and the National Institute on Aging (grant AG13196), US National Institutes of Health; the Agency for Health Care Policy Research (grant HS06516); and the John D. and Catherine T. MacArthur Foundation Research Networks on Successful Midlife Development and Socioeconomic Status and Health. J. E. F. is supported by the Medical Research Council (grant G8802774), M. J. S. by a grant from the British Heart Foundation, and M. G. M. by a Medical Research Council research professorship.

The authors thank all participating Civil Service departments and their welfare, personnel, and establishment officers; the Occupational Health and Safety Agency; the Council of Civil Service Unions; and all members of the Whitehall II Study team.

F. P. C. holds the Cephalon Chair, an endowed post at Warwick Medical School, the result of a donation from Cephalon, Inc. (Frazer, Pennsylvania). The appointment to the Chair was made entirely independently of the company, and the post holder is free to devise his own program of research. Cephalon does not have any stake in intellectual property associated with the post holder, and the Chair has complete academic independence from the company.


   References
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 

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