Email updates

Keep up to date with the latest news and content from BMC Public Health and BioMed Central.

Open Access Research article

Interaction of sleep quality and psychosocial stress on obesity in African Americans: the Cardiovascular Health Epidemiology Study (CHES)

Aurelian Bidulescu1*, Rebecca Din-Dzietham1, Dorothy L Coverson1, Zhimin Chen1, Yuan-Xiang Meng1, Sarah G Buxbaum2, Gary H Gibbons1 and Verna L Welch1

Author Affiliations

1 Morehouse School of Medicine, Atlanta, GA, USA

2 Jackson State University, Jackson, MS, USA

For all author emails, please log on.

BMC Public Health 2010, 10:581  doi:10.1186/1471-2458-10-581

The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1471-2458/10/581


Received:14 April 2010
Accepted:28 September 2010
Published:28 September 2010

© 2010 Bidulescu et al; licensee BioMed Central Ltd.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background

Compared with whites, sleep disturbance and sleep deprivation appear more prevalent in African Americans (AA). Long-term sleep deprivation may increase the risk of obesity through multiple metabolic and endocrine alterations. Previous studies have reported contradictory results on the association between habitual sleep duration and obesity. Accordingly, we aimed to assess whether sleep quality and duration are inversely associated with body mass index (BMI) and obesity and test whether these associations are modified by psychosocial stress, known to influence sleep quality.

Methods

A sample of 1,515 AA residents of metropolitan Atlanta, aged 30-65 years, was recruited by a random-digit-dialing method in 2007-08. The outcome obesity was defined by BMI (kg/m2) continuously and categorically (BMI ≥ 30 versus BMI < 30). Global sleep quality (GSQ) score was computed as the sum of response values for the seven components of the Pittsburgh Sleep Quality Index (PSQI) scale. GSQ score was defined as a continuous variable (range 0-21) and as tertiles. The general perceived stress (GPS), derived from the validated Cohen scale, was categorized into tertiles to test the interaction. Chi-square tests, correlation coefficients and weighted multiple linear and logistic regression were used to assess the associations of GSQ, GPS and obesity.

Results

The mean (standard deviation) age was 47.5 (17.0) years, and 1,096 (72%) were women. GSQ score categorized into tertiles was associated with BMI. Among women, after multivariable adjustment that included age, gender, physical activity, smoking status, education, total family income, financial stress and history of hypertension, hypercholesterolemia, diabetes and myocardial infarction, obesity was associated with sleep quality as assessed by GSQ continuous score, [odds ratio, OR (95% C.I.): 1.08 (1.03 - 1.12)], and with a worse sleep disturbance subcomponent score [OR (95% C.I.): 1.48 (1.16 - 1.89)]. Among all participants, stress modified the association between obesity and sleep quality; there was an increased likelihood of obesity in the medium stress category, OR (95% C.I.): 1.09 (1.02 - 1.17).

Conclusion

Sleep quality was associated with obesity in women. The association of sleep quality with obesity was modified by perceived stress. Our results indicate the need for simultaneous assessment of sleep and stress.

Background

Long-term sleep deprivation may increase the risk of obesity through multiple metabolic and endocrine alterations [1-11]. Previous studies have showed that, compared with whites, African Americans (AA) have greater sleep deprivation as well as more sleep disturbance [12-16]. Along with the resulting increase in obesity, they threaten to widen the racial disparity in cardiovascular disease (CVD). Studies such as Whitehall II[17] and Sleep Heart Health Study[18] found no association between habitual sleep duration and obesity, whereas other studies such as NHANES I[19], the Zurich cohort[20], CARDIA[16] and the Nurses Health Study[21] suggested the contrary. Generalizability of these findings is questionable because those cohorts' participants, with the exception of NHANES, had normal or high-normal weight.

Known to have an increased prevalence in AA[22], psychosocial stress has also been associated with CVD[23] and obesity[24] in both whites and AA [25,26]. Interestingly, the literature on stress and sleep deprivation indicates that there might be a bidirectional relationship between these two variables ([27,28]). With the high prevalence of long-term sleep deprivation, the known adverse effects of psychosocial stress on cardiovascular disease may have a more detrimental effect if proven to interact with sleep deprivation [29,30]. Consequently our aim was to test whether habitual sleep is inversely correlated with body mass index (BMI) and obesity. We also aimed to test whether the above putative association is modified by psychosocial stress, i.e., the association between sleep and BMI varies by levels of stress. We also tested the individual sleep components' association with obesity separately by gender because gender is known to be associated with sleep disturbance [31-33].

Methods

The Cardiovascular Health Epidemiology Study (CHES) includes a random sample of 1,515 AA residents in four counties of the metropolitan Atlanta area. The participants were aged 30-65 years and recruited in 2007-2008 through a random-digit-dialing (RDD) method for telephone survey of health behaviors. The RDD was conducted by the Southern Research Group, a contractor experienced with national telephone surveys including surveys sponsored by the Centers for Disease Control. Neighborhood median income was used as a stratifying variable to more efficiently evaluate the within-ethnic group effect of neighborhood characteristics, yielding 8 sampling frames. U.S. Census information[34] was thus used to obtain our weighted study sample.

The outcome variable obesity was defined by BMI (kg/m2), categorically (BMI ≥ 30, defining obesity; BMI between 25 and 30, corresponding to overweight, and BMI < 25, defining normal weight) and continuously, using the self-reported height and weight. Global sleep quality (GSQ) score, the exposure variable, was computed as the sum of response values for the seven components of the Pittsburgh Sleep Quality Index (PSQI) scale[35] (sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbance, use of sleeping medication and daytime dysfunction). The GSQ score was defined as a continuous variable (range 0-21, with higher scores reflective of poorer sleep quality) and as a trichotomous variable using the tertiles (obtained using ranking with ties). The individual PSQI components were also evaluated. Sleep duration was assessed using the third component of the Pittsburgh questionnaire that queried how many hours of actual sleep the participants got at night during the previous month. We composed two variables, one that used the actual number of hours (sleep duration as a continuous variable) and one that used the sleep duration categories defined by the Pittsburgh Sleep Quality component: more than 7 hours, between 6 and 7 hours, between 5 and 6 hours and less than 5 hours. The general perceived stress (GPS) was composed using the 14 questions from the validated Cohen scale (with a range of 0 to 64 points, with higher scores indicating higher stress)[36], and categorized into tertiles to test the interaction. Total family income was categorized into four categories: less than $25,000, between $25,000 and $49,999, between $50,000 and $74,999 and $75,000 or more. Financial stress was composed using a scale[37,38] composed of 5 questions (with a range of 0 to 12 points, with higher scores indicating higher stress), scale that was validated previously in surveys such as NHANES. Additional self-reported covariates that were included in the study included age, gender, physical activity (dichotomized, yes or no), smoking (current, former or non-smoker), education (categorized in three categories, less, equal and more than a high school education) and CVD comorbidity (self-reported history of hypertension, diabetes, hypercholesterolemia or myocardial infarction). Physical activity was queried (yes or no) with the question: "During the past month, other than your regular job, did you participate in any physical activities or exercises such as running, calisthenics, golf, gardening, or walking for exercise?"

The study was approved by the Morehouse School of Medicine's Institutional Review Board. Verbal informed consent was also obtained from the study participants by SRG before initiating the survey.

To assess the association between the variables considered in our analyses, Spearman correlation coefficients were used to account for the categorical nature of the PSQI components. Chi-square tests were used to assess the statistical significance between the categories. Tests for interaction between gender and global sleep quality general score and PSQI subcomponents were used to examine whether the association of obesity with each correlate differed between men and women. Weighted multiple linear and logistic regression models were also used to assess the independent association of GSQ score and obesity, adjusting for covariates and calculating correct variances given the complex weighted structure of the study sample. The association between the actual number of hours of sleep and obesity was also assessed. Statistical significance was set at p < 0.05 for the main and the interactive effects. SAS statistical software version 9.2 (with its survey procedures) was used for the analysis (SAS Institute Inc., Cary, NC, USA).

Results

In our sample of exclusively AA, the mean (standard deviation; SD) age was 47.5 (17.0). For BMI, the mean (SD) was 29.4 (7.1). 557 participants (36.6%) were younger than 50 years of age and 1,096 (72%) were women. Fifty percents of those surveyed reported sub-optimal sleep (duration < 6 hours/night). Over 50% of respondents had poor quality sleep (GSQ score > 5).

The main characteristics of study participants by tertiles of GSQ, by tertiles of GPS and by sleep duration are presented in Table 1; with few exceptions such as age, hypertension and diabetes, there was a significant association between those characteristics (such as gender, physical activity, education, history of myocardial infarction, financial stress and family income) and sleep quality. Obesity was highly significantly associated with GSQ (p < 0.0001). There was an association between sleep duration and age, categorized BMI (p = 0.03), smoking status, physical activity and history of diabetes and myocardial infarction (Table 1). Sleep duration was also highly associated with financial stress and total family income (Table 1). GPS was associated with age, smoking status, physical activity, education, history of myocardial infarction, financial stress and family income (Table 1).

Table 1. Characteristics of study participants according to global sleep quality, general perceived stress and sleep duration*

GSQ continuous score was modestly but significantly associated with BMI continuous, (a correlation coefficient, r = 0.13; indicating a worse global sleep quality associated with a higher BMI), and moderately and significantly with GPS, r = 0.36, indicating a higher global perceived stress associated with a worse sleep quality (Table 2). Sleep duration (continuous) and use of sleeping medications showed a modest association with BMI (Table 2). Sleep duration, sleep latency and use of sleeping medication showed a moderate association with GPS (Table 2). BMI had a moderate association with sleep disturbances (r = 0.33, p < 0.0001) and daytime dysfunction (r = 0.35, p < 0.0001). The partial correlations (with adjustment for age and gender) between GSQ and BMI was 0.19 (p < 0.0001), and between GPS and BMI was 0.09 (p = 0.001).

Table 2. Correlation coefficients between the main variables

The multivariable-adjusted odds ratios of obesity for the sleep quality components are presented in Table 3. Gender was an effect modifier of the association between habitual sleep efficiency (p = 0.02) and daytime dysfunction (p = 0.04) with obesity (Table 3). Among women, after adjustment for age, physical activity, smoking status, education and history of hypertension, hypercholesterolemia, diabetes and myocardial infarction, there was an increased likelihood of obesity for those participants with a higher (worse) sleep disturbance score [OR (95% C.I.): 1.56 (1.24 - 1.97)] and with a higher (worse) daytime dysfunction score [OR (95% C.I.): 1.39 (1.10 - 1.76)]. For sleep disturbance, the odds ratios remained significant after further adjustment for general perceived stress [OR (95% C.I.): 1.55 (1.22 - 1.98)] or for total family income, [OR (95% C.I.): 1.48 (1.16 - 1.89)] (Table 3). For daytime dysfunction, the odds ratios remained significant after further adjustment for GPS, but not after further adjustment for total family income (Table 3).

Table 3. Multivariable-adjusted odds ratios of obesity for sleep quality domains by gender

After multivariable adjustment that included age, gender, physical activity, smoking status, education, total family income, financial stress and history of hypertension, hypercholesterolemia, diabetes and myocardial infarction, sleep quality as assessed by GSQ continuous score showed an association with obesity among women [OR (95% C.I.): 1.08 (1.03 - 1.12)] but not among men [OR (95% C.I.): 0.98 (0.89 - 1.09)]. Continuous BMI showed an association with GPS (p = 0.02) when categorized into tertiles.

In crude models, GSQ categorized score did not interact with GPS (categorized into tertiles) to significantly increase the likelihood of obesity (p = 0.85). However, GPS categorized positively interacted with GSQ continuous to significantly increase the likelihood of obesity (p = 0.02). Our data suggest that there was an increased likelihood of obesity in the medium stressed participants (odds ratio of 1.09 [1.02 - 1.17]) compared to the other two groups (1.01 [0.94 - 1.10], for low stress, and 1.03 [0.97 - 1.10], for high stress), and therefore stress appears to modulate the association between obesity and sleep quality.

After adjustment for age, gender, physical activity, smoking status, education, financial stress, total family income and history of hypertension, hypercholesterolemia, diabetes and myocardial infarction, no significant interactions were detected between stress and the PSQI components on obesity.

Discussion

In our cross-sectional investigation we found that global sleep quality and sleep duration were associated with categorized body mass index (normal weight, overweight and obesity). In women but not in men, after multivariable adjustment, sleep quality as assessed by the global sleep quality continuous score showed an association with obesity. Among women, sleep disturbance and daytime dysfunction, two of the PSQI components, were also significantly associated with obesity in multivariable-adjusted models. The association of continuous sleep quality with obesity was modified by perceived stress categorized into tertiles. There appears to be an increased likelihood of obesity in the medium stress group of participants compared with the other two groups.

Sleep disorders are prevalent and yet underexplored [39]. According to the National Sleep Foundation survey, 39% of American adults obtain less than the recommended 7 hours of sleep per weeknight [40]. Obstructive sleep apnea, for example, is a very common disease whose population prevalence is comparable to that of other chronic diseases such as asthma, chronic obstructive pulmonary disease, type 2 diabetes and coronary heart disease [41]. Sleep disturbance appears to be more prevalent in African Americans than whites [15,16,39,42]. Therefore, our finding that half of the participants reported sleeping less than six hours per night was an anticipated result. Noteworthy was the association of gender, physical activity, smoking, education, financial stress, family income and history of myocardial infarction with sleep quality, in concordance with previous studies [43,44]. As gender has been previously associated with sleep disturbance[31-33], the emergence of gender as an effect modifier for the association of obesity with GSQ and PSQI components was not surprising.

Research suggests chronic sleep restriction impairs cognitive function as well as influence cardiovascular and metabolic health [30]. Sleep deprivation has several adverse physiological consequences, including impaired glucose tolerance and insulin sensitivity, elevated sympathetic tone, increased inflammation, and the increase of ghrelin and the decrease of leptin with the subsequent increase of hunger and appetite [45-50]. There is a growing body of literature that places sleep disorders upstream on the causal pathway of obesity [19,51-53]. In multivariate analyses including adjustment for BMI, both the Nurses Health Study as well as the NHANES identified short sleep as a risk factor for incident diabetes [54,55]. As obesity is distributed differentially by ethnic groups and given its burden is growing, an increase of sleep disorders may further deepen the ethnic disparity in obesity-related cardiovascular disease (CVD). The comparison of our study with studies such as NHANES I[19], Zurich cohort[20], CARDIA[16] and Nurses Health Study[21] that reported an association between sleep duration and obesity is challenging as those cohorts' participants have a lower average BMI.

Psychosocial stress, which has been shown to affect cardiovascular endpoints differently in ethnic minorities [56-59], was also shown to be inversely associated with quality of sleep [27,28]. When sleep quality global score was considered continuous, we found an interaction between sleep quality and stress. There appears to be an increased risk of obesity in the medium stress group compared to the other two groups. To our knowledge, the other few studies that assessed both sleep quality and psychological stress[60-62] did not consider their interaction. Our data suggest that stress may modulate the association between obesity and sleep quality. Total family income and financial stress were also associated with sleep duration in accordance with previous studies [63]. Moreover, general perceived stress and financial stress diminished the significant associations of sleep disturbance and daytime dysfunction with obesity to the point of non-significance, suggesting that stress mediates the association between these PSQI components and obesity. Therefore, simultaneous assessment of general stress and financial stress should be attempted when investigating the association of sleep components with obesity.

Questionnaires such as Berlin questionnaire[64,65] or Pittsburgh questionnaire remain the instruments of choice for telephone surveys and epidemiological studies without clinical exams, for which a more objective sleep assessment using polysomnography or actigraphy devices would be desirable. Our finding that only two of the PSQI domains, sleep disturbance and daytime dysfunction, were associated with obesity in multivariable-adjusted models indicate the need for a full query of sleep quality domains.

The current study is among the first to assess in AA the interaction of sleep quality with psychosocial stress on obesity with adjustment for physical activity, a major correlate of obesity, albeit a limited physical activity assessment (which constitutes one of the main limitation of our investigation). Similarly with other telephone surveys, the majority of respondents were female which limits the generalizability to AA males. Other notable limitations are the facts that BMI and sleep assessment are only self-reported measures and there was no dietary intake information or depression symptoms collected. Among the strengths of our investigation are a thorough assessment of psychosocial and financial stress and a complete Pittsburgh sleep questionnaire.

Epidemiological research shows that short self-reported sleep duration is associated with several endpoints such as diabetes, coronary heart disease and mortality [18,30]. Part of these associations might be mediated by obesity. Existing data have variable consistency. Twenty years after the development of the Pittsburgh Sleep Quality Index, few other questionnaires have been specifically designed to measure sleep quality. The PSQI remains a sensitive tool when queried entirely and when used in conjunction with assessments of different types of stress.

Conclusions

The association of sleep quality with obesity was modified by perceived stress; among those with medium stress, there was an association between sleep quality and obesity. Simultaneous assessments of sleep and stress should be performed whenever possible.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

AB, RD-D and VLW conceived of and designed the study. AB and ZC performed the statistical analyses. AB, RD-D, DLC, SGB, GHG and VLW interpreted the results. AB, RD-D and VLW drafted the manuscript. All authors revised the manuscript for intellectual content, and read and approved the final manuscript.

Acknowledgements

Financial support for this study came from NIH grants 5-UH1-HL073461-04 and 5-U54-RR022814 (MSM-CCRE). The findings of this study are solely the responsibility of the authors and do not necessarily represent the official views of NCRR or NHLBI.

The investigators thank CHES study participants and SRG staff for their valuable contributions.

The results described in this article have been presented in part during the American Heart Association Epidemiology Council National Scientific Conference, March 2009 in Tampa, Florida.

References

  1. Bose M, Olivan B, Laferrere B: Stress and obesity: the role of the hypothalamic-pituitary-adrenal axis in metabolic disease.

    Curr Opin Endocrinol Diabetes Obes 2009, 16:340-346. PubMed Abstract | PubMed Central Full Text OpenURL

  2. Jun J, Polotsky VY: Metabolic consequences of sleep-disordered breathing.

    Ilar J 2009, 50:289-306. PubMed Abstract OpenURL

  3. Van Cauter E, Spiegel K, Tasali E, Leproult R: Metabolic consequences of sleep and sleep loss.

    Sleep Med 2008, 9(Suppl 1):S23-28. PubMed Abstract | Publisher Full Text OpenURL

  4. Penev PD: Sleep deprivation and energy metabolism: to sleep, perchance to eat?

    Curr Opin Endocrinol Diabetes Obes 2007, 14:374-381. PubMed Abstract | Publisher Full Text OpenURL

  5. Taheri S: Sleep and metabolism: bringing pieces of the jigsaw together.

    Sleep Med Rev 2007, 11:159-162. PubMed Abstract | Publisher Full Text OpenURL

  6. Knutson KL, Spiegel K, Penev P, Van Cauter E: The metabolic consequences of sleep deprivation.

    Sleep Med Rev 2007, 11:163-178. PubMed Abstract | Publisher Full Text | PubMed Central Full Text OpenURL

  7. Van Cauter E, Holmback U, Knutson K, Leproult R, Miller A, Nedeltcheva A, Pannain S, Penev P, Tasali E, Spiegel K: Impact of sleep and sleep loss on neuroendocrine and metabolic function.

    Horm Res 2007, 67(Suppl 1):2-9. PubMed Abstract | Publisher Full Text OpenURL

  8. Copinschi G: Metabolic and endocrine effects of sleep deprivation.

    Essent Psychopharmacol 2005, 6:341-347. PubMed Abstract OpenURL

  9. Svatikova A, Wolk R, Gami AS, Pohanka M, Somers VK: Interactions between obstructive sleep apnea and the metabolic syndrome.

    Curr Diab Rep 2005, 5:53-58. PubMed Abstract | Publisher Full Text OpenURL

  10. Spiegel K, Tasali E, Leproult R, Van Cauter E: Effects of poor and short sleep on glucose metabolism and obesity risk.

    Nat Rev Endocrinol 2009, 5:253-261. PubMed Abstract | Publisher Full Text OpenURL

  11. Leproult R, Van Cauter E: Role of Sleep and Sleep Loss in Hormonal Release and Metabolism.

    Endocr Dev 2010, 17:11-21. PubMed Abstract | Publisher Full Text OpenURL

  12. Knutson KL, Van Cauter E, Rathouz PJ, DeLeire T, Lauderdale DS: Trends in the prevalence of short sleepers in the USA: 1975-2006.

    Sleep 33:37-45. PubMed Abstract | PubMed Central Full Text OpenURL

  13. Nunes J, Jean-Louis G, Zizi F, Casimir GJ, von Gizycki H, Brown CD, McFarlane SI: Sleep duration among black and white Americans: results of the National Health Interview Survey.

    J Natl Med Assoc 2008, 100:317-322. PubMed Abstract OpenURL

  14. Hale L, Do DP: Racial differences in self-reports of sleep duration in a population-based study.

    Sleep 2007, 30:1096-1103. PubMed Abstract | PubMed Central Full Text OpenURL

  15. Hiestand DM, Britz P, Goldman M, Phillips B: Prevalence of symptoms and risk of sleep apnea in the US population: Results from the national sleep foundation sleep in America 2005 poll.

    Chest 2006, 130:780-786. PubMed Abstract | Publisher Full Text OpenURL

  16. Lauderdale DS, Knutson KL, Yan LL, Rathouz PJ, Hulley SB, Sidney S, Liu K: Objectively measured sleep characteristics among early-middle-aged adults: the CARDIA study.

    Am J Epidemiol 2006, 164:5-16. PubMed Abstract | Publisher Full Text OpenURL

  17. Stranges S, Cappuccio FP, Kandala NB, Miller MA, Taggart FM, Kumari M, Ferrie JE, Shipley MJ, Brunner EJ, Marmot MG: 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, 167:321-329. PubMed Abstract | Publisher Full Text OpenURL

  18. Gottlieb DJ, Punjabi NM, Newman AB, Resnick HE, Redline S, Baldwin CM, Nieto FJ: Association of sleep time with diabetes mellitus and impaired glucose tolerance.

    Arch Intern Med 2005, 165:863-867. PubMed Abstract | Publisher Full Text OpenURL

  19. Gangwisch JE, Malaspina D, Boden-Albala B, Heymsfield SB: Inadequate sleep as a risk factor for obesity: analyses of the NHANES I.

    Sleep 2005, 28:1289-1296. PubMed Abstract OpenURL

  20. Hasler G, Buysse DJ, Klaghofer R, Gamma A, Ajdacic V, Eich D, Rossler W, Angst J: The association between short sleep duration and obesity in young adults: a 13-year prospective study.

    Sleep 2004, 27:661-666. PubMed Abstract OpenURL

  21. Patel SR, Malhotra A, White DP, Gottlieb DJ, Hu FB: Association between reduced sleep and weight gain in women.

    Am J Epidemiol 2006, 164:947-954. PubMed Abstract | Publisher Full Text OpenURL

  22. Kumanyika S, Adams-Campbell LL: Obesity, diet, and psychosocial factors contributing to cardiovascular disease in blacks.

    Cardiovasc Clin 1991, 21:47-73. PubMed Abstract OpenURL

  23. Lahiri K, Rettig-Ewen V, Bohm M, Laufs U: Perceived psychosocial stress and cardiovascular risk factors in obese and non-obese patients.

    Clin Res Cardiol 2007, 96:365-374. PubMed Abstract | Publisher Full Text OpenURL

  24. Block JP, He Y, Zaslavsky AM, Ding L, Ayanian JZ: Psychosocial stress and change in weight among US adults.

    Am J Epidemiol 2009, 170:181-192. PubMed Abstract | Publisher Full Text | PubMed Central Full Text OpenURL

  25. Fowler-Brown AG, Bennett GG, Goodman MS, Wee CC, Corbie-Smith GM, James SA: Psychosocial stress and 13-year BMI change among blacks: the Pitt County Study.

    Obesity (Silver Spring) 2009, 17:2106-2109. PubMed Abstract | Publisher Full Text OpenURL

  26. Anand SS, Islam S, Rosengren A, Franzosi MG, Steyn K, Yusufali AH, Keltai M, Diaz R, Rangarajan S, Yusuf S: Risk factors for myocardial infarction in women and men: insights from the INTERHEART study.

    Eur Heart J 2008, 29:932-940. PubMed Abstract | Publisher Full Text OpenURL

  27. Akerstedt T: Psychosocial stress and impaired sleep.

    Scand J Work Environ Health 2006, 32:493-501. PubMed Abstract | Publisher Full Text OpenURL

  28. Kim EJ, Dimsdale JE: The effect of psychosocial stress on sleep: a review of polysomnographic evidence.

    Behav Sleep Med 2007, 5:256-278. PubMed Abstract OpenURL

  29. Vgontzas AN, Lin HM, Papaliaga M, Calhoun S, Vela-Bueno A, Chrousos GP, Bixler EO: Short sleep duration and obesity: the role of emotional stress and sleep disturbances.

    Int J Obes (Lond) 2008, 32:801-809. PubMed Abstract | Publisher Full Text OpenURL

  30. Malhotra A, Loscalzo J: Sleep and cardiovascular disease: an overview.

    Prog Cardiovasc Dis 2009, 51:279-284. PubMed Abstract | Publisher Full Text | PubMed Central Full Text OpenURL

  31. Krishnan V, Collop NA: Gender differences in sleep disorders.

    Curr Opin Pulm Med 2006, 12:383-389. PubMed Abstract | Publisher Full Text OpenURL

  32. Nordin M, Knutsson A, Sundbom E, Stegmayr B: Psychosocial factors, gender, and sleep.

    J Occup Health Psychol 2005, 10:54-63. PubMed Abstract | Publisher Full Text OpenURL

  33. Collop NA, Adkins D, Phillips BA: Gender differences in sleep and sleep-disordered breathing.

    Clin Chest Med 2004, 25:257-268. PubMed Abstract | Publisher Full Text OpenURL

  34. DeNavas-Walt C, Proctor BD, Lee CH: Income, poverty, and health insurance coverage in the United States: 2004.

    US Census Bureau, Current Population Reports, P 2005., 60 OpenURL

  35. Buysse DJ, Reynolds CF, Monk TH, Berman SR, Kupfer DJ: The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research.

    Psychiatry Res 1989, 28:193-213. PubMed Abstract | Publisher Full Text OpenURL

  36. Cohen S, Kamarck T, Mermelstein R: A global measure of perceived stress.

    J Health Soc Behav 1983, 24:385-396. PubMed Abstract | Publisher Full Text OpenURL

  37. Pearlin LI, Lieberman MA, Menaghan EG, Mullan JT: The stress process.

    J Health Soc Behav 1981, 22:337-356. PubMed Abstract | Publisher Full Text OpenURL

  38. Krause N: Chronic financial strain, social support, and depressive symptoms among older adults.

    Psychol Aging 1987, 2:185-192. PubMed Abstract | Publisher Full Text OpenURL

  39. Krueger PM, Friedman EM: Sleep duration in the United States: a cross-sectional population-based study.

    Am J Epidemiol 2009, 169:1052-1063. PubMed Abstract | Publisher Full Text | PubMed Central Full Text OpenURL

  40. 2002 Sleep in America Poll [http://www.sleepfoundation.org/sites/default/files/2002SleepInAmericaPoll.pdf] webcite

  41. Madani M, Madani F: Epidemiology, pathophysiology, and clinical features of obstructive sleep apnea.

    Oral Maxillofac Surg Clin North Am 2009, 21:369-375. PubMed Abstract | Publisher Full Text OpenURL

  42. Ancoli-Israel S, Klauber MR, Stepnowsky C, Estline E, Chinn A, Fell R: Sleep-disordered breathing in African-American elderly.

    Am J Respir Crit Care Med 1995, 152:1946-1949. PubMed Abstract OpenURL

  43. Watenpaugh DE: The role of sleep dysfunction in physical inactivity and its relationship to obesity.

    Curr Sports Med Rep 2009, 8:331-338. PubMed Abstract OpenURL

  44. Lexcen FJ, Hicks RA: Does cigarette smoking increase sleep problems.

    Percept Mot Skills 1993, 77:16-18. PubMed Abstract OpenURL

  45. Saaresranta T, Polo O: Does leptin link sleep loss and breathing disturbances with major public diseases?

    Ann Med 2004, 36:172-183. PubMed Abstract | Publisher Full Text OpenURL

  46. van Leeuwen WM, Lehto M, Karisola P, Lindholm H, Luukkonen R, Sallinen M, Harma M, Porkka-Heiskanen T, Alenius H: Sleep restriction increases the risk of developing cardiovascular diseases by augmenting proinflammatory responses through IL-17 and CRP.

    PLoS One 2009, 4:e4589. PubMed Abstract | Publisher Full Text | PubMed Central Full Text OpenURL

  47. Spiegel K, Leproult R, Van Cauter E: Impact of sleep debt on metabolic and endocrine function.

    Lancet 1999, 354:1435-1439. PubMed Abstract | Publisher Full Text OpenURL

  48. Spiegel K, Leproult R, L'Hermite-Baleriaux M, Copinschi G, Penev PD, Van Cauter E: Leptin levels are dependent on sleep duration: relationships with sympathovagal balance, carbohydrate regulation, cortisol, and thyrotropin.

    J Clin Endocrinol Metab 2004, 89:5762-5771. PubMed Abstract | Publisher Full Text OpenURL

  49. Meier-Ewert HK, Ridker PM, Rifai N, Regan MM, Price NJ, Dinges DF, Mullington JM: Effect of sleep loss on C-reactive protein, an inflammatory marker of cardiovascular risk.

    J Am Coll Cardiol 2004, 43:678-683. PubMed Abstract | Publisher Full Text OpenURL

  50. Mullington JM, Chan JL, Van Dongen HP, Szuba MP, Samaras J, Price NJ, Meier-Ewert HK, Dinges DF, Mantzoros CS: Sleep loss reduces diurnal rhythm amplitude of leptin in healthy men.

    J Neuroendocrinol 2003, 15:851-854. PubMed Abstract | Publisher Full Text OpenURL

  51. Patel SR, Hu FB: Short sleep duration and weight gain: a systematic review.

    Obesity (Silver Spring) 2008, 16:643-653. PubMed Abstract | Publisher Full Text | PubMed Central Full Text OpenURL

  52. Spiegel K: Sleep loss as a risk factor for obesity and diabetes.

    Int J Pediatr Obes 2008, 3(Suppl 2):27-28. PubMed Abstract | Publisher Full Text OpenURL

  53. Al Lawati NM, Patel SR, Ayas NT: Epidemiology, risk factors, and consequences of obstructive sleep apnea and short sleep duration.

    Prog Cardiovasc Dis 2009, 51:285-293. PubMed Abstract | Publisher Full Text OpenURL

  54. Ayas NT, White DP, Al-Delaimy WK, Manson JE, Stampfer MJ, Speizer FE, Patel S, Hu FB: A prospective study of self-reported sleep duration and incident diabetes in women.

    Diabetes Care 2003, 26:380-384. PubMed Abstract | Publisher Full Text OpenURL

  55. Gangwisch JE, Heymsfield SB, Boden-Albala B, Buijs RM, Kreier F, Pickering TG, Rundle AG, Zammit GK, Malaspina D: Sleep duration as a risk factor for diabetes incidence in a large U.S. sample.

    Sleep 2007, 30:1667-1673. PubMed Abstract | PubMed Central Full Text OpenURL

  56. Krieger N: Does racism harm health? Did child abuse exist before 1962? On explicit questions, critical science, and current controversies: an ecosocial perspective.

    Am J Public Health 2008, 98:S20-25. PubMed Abstract | Publisher Full Text | PubMed Central Full Text OpenURL

  57. Pointer MA, Livingston JN, Yancey S, McClelland MK, Bukoski RD: Psychosocial factors contribute to resting blood pressure in African Americans.

    Ethn Dis 2008, 18:289-293. PubMed Abstract OpenURL

  58. Brondolo E, Gallo LC, Myers HF: Race, racism and health: disparities, mechanisms, and interventions.

    J Behav Med 2009, 32:1-8. PubMed Abstract | Publisher Full Text OpenURL

  59. Bixler E: Sleep and society: an epidemiological perspective.

    Sleep Med 2009, 10(Suppl 1):S3-6. PubMed Abstract | Publisher Full Text OpenURL

  60. Algul A, Ates MA, Semiz UB, Basoglu C, Ebrinc S, Gecici O, Gulsun M, Kardesoglu E, Cetin M: Evaluation of general psychopathology, subjective sleep quality, and health-related quality of life in patients with obesity.

    Int J Psychiatry Med 2009, 39:297-312. PubMed Abstract | Publisher Full Text OpenURL

  61. Nilsson PM, Nilsson JA, Hedblad B, Berglund G: Sleep disturbance in association with elevated pulse rate for prediction of mortality--consequences of mental strain?

    J Intern Med 2001, 250:521-529. PubMed Abstract | Publisher Full Text OpenURL

  62. Marniemi J, Kronholm E, Aunola S, Toikka T, Mattlar CE, Koskenvuo M, Ronnemaa T: Visceral fat and psychosocial stress in identical twins discordant for obesity.

    J Intern Med 2002, 251:35-43. PubMed Abstract | Publisher Full Text OpenURL

  63. Hall M, Buysse DJ, Nofzinger EA, Reynolds CF, Thompson W, Mazumdar S, Monk TH: Financial strain is a significant correlate of sleep continuity disturbances in late-life.

    Biol Psychol 2008, 77:217-222. PubMed Abstract | Publisher Full Text | PubMed Central Full Text OpenURL

  64. Phillips B, Cook Y, Schmitt F, Berry D: Sleep apnea: prevalence of risk factors in a general population.

    South Med J 1989, 82:1090-1092. PubMed Abstract | Publisher Full Text OpenURL

  65. Netzer NC, Stoohs RA, Netzer CM, Clark K, Strohl KP: Using the Berlin Questionnaire to identify patients at risk for the sleep apnea syndrome.

    Ann Intern Med 1999, 131:485-491. PubMed Abstract | Publisher Full Text OpenURL

Pre-publication history

The pre-publication history for this paper can be accessed here:

http://www.biomedcentral.com/1471-2458/10/581/prepub