Epidemiology and Population Health

High sleep variability predicts a blunted weight loss response and short sleep duration a reduced decrease in waist circumference in the PREDIMED-Plus Trial

Abstract

Background

Whether short sleep duration or high sleep variability may predict less weight loss and reduction in measures of adiposity in response to lifestyle interventions is unknown. The aim of this study was to compare the 12-month changes in weight and adiposity measures between those participants with short or adequate sleep duration and those with low or high sleep variability (intra-subject standard deviation of the sleep duration) in PREvención con DIeta MEDiterránea (PREDIMED)-Plus, a primary prevention trial based on lifestyle intervention programs.

Methods

Prospective analysis of 1986 community-dwelling subjects (mean age 65 years, 47% females) with overweight/obesity and metabolic syndrome from the PREDIMED-Plus trial was conducted. Accelerometry-derived sleep duration and sleep variability and changes in average weight, body mass index (BMI), and waist circumference (WC) attained after 12-month interventions were analyzed.

Results

The adjusted difference in 12-month changes in weight and BMI in participants in the third tertile of sleep variability was 0.5 kg (95% CI 0.1 to 0.9; p = 0.021) and 0.2 kg/m2 (0.04 to 0.4; p = 0.015), respectively, as compared with participants in the first tertile. The adjusted difference in 12-month changes from baseline in WC was −0.8 cm (−1.5 to −0.01; p = 0.048) in participants sleeping <6 h, compared with those sleeping between 7 and 9 h.

Conclusions

Our findings suggest that the less variability in sleep duration or an adequate sleep duration the greater the success of the lifestyle interventions in adiposity.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

References

  1. 1.

    Ogilvie RP, Patel SR. The epidemiology of sleep and obesity. Sleep Health. 2017;3:383–8.

    Article  PubMed  PubMed Central  Google Scholar 

  2. 2.

    Chaput JP, Després JP, Bouchard C, Tremblay A. Association of sleep duration with type 2 diabetes and impaired glucose tolerance. Diabetologia. 2007;50:2298–304.

    Article  PubMed  PubMed Central  Google Scholar 

  3. 3.

    Sperry SD, Scully ID, Gramzow RH, Jorgensen RS. Sleep duration and waist circumference in adults: a meta-analysis. Sleep. 2015;38:1269–76.

    Article  PubMed  PubMed Central  Google Scholar 

  4. 4.

    Xiao Q, Gu F, Caporaso N, Matthews CE. Relationship between sleep characteristics and measures of body size and composition in a nationally-representative sample. BMC Obes. 2016;3:48.

    Article  PubMed  PubMed Central  Google Scholar 

  5. 5.

    Rosique-Esteban N, Papandreou C, Romaguera D, Warnberg J, Corella D, Martínez-González MÁ, et al. Cross-sectional associations of objectively-measured sleep characteristics with obesity and type 2 diabetes in the PREDIMED-Plus trial. Sleep. 2018. https://doi.org/10.1093/sleep/zsy190.

  6. 6.

    Lopez-Garcia E, Faubel R, Leon-Muñoz L, Zuluaga MC, Banegas JR, Rodriguez-Artalejo F. Sleep duration, general and abdominal obesity, and weight change among the older adult population of Spain. Am J Clin Nutr. 2008;6:310–6.

    Article  Google Scholar 

  7. 7.

    Chaput JP, Després JP, Bouchard C, Tremblay A. The association between sleep duration and weight gain in adults: a 6-year prospective study from the Quebec Family Study. Sleep. 2008;31:517–23.

    Article  PubMed  PubMed Central  Google Scholar 

  8. 8.

    Appelhans BM, Janssen I, Cursio JF, Matthews KA, Hall M, Gold EB, et al. Sleep duration and weight change in midlife women: the SWAN sleep study. Obesity. 2013;21:77–84.

    Article  PubMed  PubMed Central  Google Scholar 

  9. 9.

    Chaput JP, Després JP, Bouchard C, Tremblay A. Longer sleep duration associates with lower adiposity gain in adult short sleepers. Int J Obes (Lond). 2012;36:752–6.

    Article  Google Scholar 

  10. 10.

    Garaulet M, Sánchez-Moreno C, Smith CE, Lee YC, Nicolás F, Ordovás JM. Ghrelin, sleep reduction and evening preference: relationships to CLOCK 3111 T/C SNP and weight loss. PLoS ONE. 2011;6:e17435.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. 11.

    Nedeltcheva AV, Kilkus JM, Imperial J, Schoeller DA, Penev PD. Insufficient sleep undermines dietary efforts to reduce adiposity. Ann Intern Med. 2010;153:435–41.

    Article  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Hamet P, Tremblay J. Genetics of the sleep-wake cycle and its disorders. Metabolism. 2006;55(10Suppl 2):7–12.

    Article  CAS  Google Scholar 

  13. 13.

    Roenneberg T, Allebrandt KV, Merrow M, Vetter C. Social jetlag and obesity. Curr Biol. 2012;22:939–43.

    Article  CAS  Google Scholar 

  14. 14.

    Burgess HJ, Park M, Wyatt JK, Rizvydeen M, Fogg LF. Sleep and circadian variability in people with delayed sleep-wake phase disorder versus healthy controls. Sleep Med. 2017;34:33–9.

    Article  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Ogilvie RP, Redline S, Bertoni AG, Chen X, Ouyang P, Szklo M, et al. Actigraphy measured sleep indices and adiposity: the multi-ethnic study of atherosclerosis (MESA). Sleep. 2016;39:1701–8.

    Article  PubMed  PubMed Central  Google Scholar 

  16. 16.

    He F, Bixler EO, Liao J, Berg A, Imamura Kawasawa Y, Fernandez-Mendoza J, et al. Habitual sleep variability, mediated by nutrition intake, is associated with abdominal obesity in adolescents. Sleep Med. 2015;16:1489–94.

    Article  PubMed  PubMed Central  Google Scholar 

  17. 17.

    Kobayashi D, Takahashi O, Shimbo T, Okubo T, Arioka H, Fukui T. High sleep duration variability is an independent risk factor for weight gain. Sleep Breath. 2013;17:167–72.

    Article  Google Scholar 

  18. 18.

    Knutson KL, Wu D, Patel SR, Loredo JS, Redline S, Cai J, et al. Association between sleep timing, obesity, diabetes: the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) Cohort Study. Sleep. 2017. https://doi.org/10.1093/sleep/zsx014.

  19. 19.

    Taylor BJ, Matthews KA, Hasler BP, Roecklein KA, Kline CE, Buysse DJ, et al. Bedtime variability and metabolic health in midlife women: the SWAN sleep study. Sleep. 2016;39:457–65.

    Article  PubMed  PubMed Central  Google Scholar 

  20. 20.

    Wirth MD, Hébert JR, Hand GA, Youngstedt SD, Hurley TG, Shook RP, et al. Association between actigraphic sleep metrics and body composition. Ann Epidemiol. 2015;25:773–8.

    Article  PubMed  PubMed Central  Google Scholar 

  21. 21.

    Garaulet M, Corbalán MD, Madrid JA, Morales E, Baraza JC, Lee YC, et al. CLOCK gene is implicated in weight reduction in obese patients participating in a dietary programme based on the Mediterranean diet. Int J Obes (Lond). 2010;34:516–23.

    Article  CAS  Google Scholar 

  22. 22.

    Salas-Salvadó J, Díaz-López A, Ruiz-Canela M, Basora J, Fitó M, Corella D, et al. Effect of a lifestyle intervention program with energy-restricted Mediterranean diet and exercise on weight loss and cardiovascular risk factors: one-year results of the PREDIMED-Plus trial. Diabetes Care. 2018. https://doi.org/10.2337/dc18-0836.

  23. 23.

    Martínez-González MA, Buil-Cosiales P, Corella D, Bulló M, Fitó M, Vioque J, et al. Cohort profile: design and methods of the PREDIMED-Plus randomized trial. Int J Epidemiol. 2018. https://doi.org/10.1093/ije/dyy225.

  24. 24.

    Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009;120:1640–5.

    Article  CAS  Google Scholar 

  25. 25.

    van Hees VT, Fang Z, Langford J, Assah F, Mohammad A, da Silva IC, et al. Autocalibration of accelerometer data for free-living physical activity assessment using local gravity and temperature: an evaluation on four continents. J Appl Physiol (1985). 2014;117:738–44.

    Article  Google Scholar 

  26. 26.

    van Hees VT, Sabia S, Anderson KN, Denton SJ, Oliver J, Catt M, et al. A novel, open access method to assess sleep duration using a wrist-worn accelerometer. PLoS ONE. 2015;10:e0142533.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Menai M, van Hees VT, Elbaz A, Kivimaki M, Singh-Manoux A, Sabia S. Accelerometer assessed moderate-to-vigorous physical activity and successful ageing: results from the Whitehall II study. Sci Rep. 2017;8:45772.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. 28.

    World Health Organization. Global recommendations on physical activity for health. 2010. http://www.who.int/dietphysicalactivity/factsheet_olderadults/en/. Accessed 3 Apr 2018.

  29. 29.

    Grandner MA, Patel NP, Gehrman PR, Perlis ML, Pack AI. Problems associated with short sleep: bridging the gap between laboratory and epidemiological studies. Sleep Med Rev. 2010;14:239–47.

    Article  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Hirshkowitz M, Whiton K, Albert SM, Alessi C, Bruni O, DonCarlos L, et al. National Sleep Foundation’s updated sleep duration recommendations: final report. Sleep Health. 2015;1:233–43.

    Article  PubMed  PubMed Central  Google Scholar 

  31. 31.

    Patel SR, Hayes AL, Blackwell T, Evans DS, Ancoli-Israel S, Wing YK, et al. The association between sleep patterns and obesity in older adults. Int J Obes (Lond). 2014;38:1159–64.

    Article  CAS  Google Scholar 

  32. 32.

    Broussard JL, Van Cauter E. Disturbances of sleep and circadian rhythms: novel risk factors for obesity. Curr Opin Endocrinol Diabetes Obes. 2016;23:353–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Oishi K, Shirai H, Ishida N. CLOCK is involved in the circadian transactivation of peroxisome-proliferator-activated receptor alpha (PPARalpha) in mice. Biochem J. 2005;386(Pt 3):575–81.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Turek FW, Joshu C, Kohsaka A, Lin E, Ivanova G, McDearmon E, et al. Obesity and metabolic syndrome in circadian Clock mutant mice. Science. 2005;308:1043–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. 35.

    Froy O. Metabolism and circadian rhythms-implications for obesity. Endocr Rev. 2010;31:1–24.

    Article  CAS  Google Scholar 

  36. 36.

    McHill AW, Melanson EL, Higgins J, Connick E, Moehlman TM, Stothard ER, et al. Impact of circadian misalignment on energy metabolism during simulated nightshift work. Proc Natl Acad Sci USA. 2014;111:17302–17.

    Article  CAS  Google Scholar 

  37. 37.

    Messina G, De Luca V, Viggiano A. Autonomic nervous system in the control of energy balance and body weight: personal contributions. Neurol Res Int. 2013;2013:639280.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. 38.

    Zitting KM, Vujovic N, Yuan RK, Isherwood CM, Medina JE, Wang W, et al. Human resting energy expenditure varies with circadian phase. Curr Biol. 2018;28:3685–90.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. 39.

    Mattson MP, Allison DB, Fontana L, Harvie M, Longo VD, Malaisse WJ, et al. Meal frequency and timing in health and disease. Proc Natl Acad Sci USA. 2014;111:16647–53.

    Article  CAS  Google Scholar 

  40. 40.

    Garaulet M, Gómez-Abellán P, Alburquerque-Béjar JJ, Lee YC, Ordovás JM, Scheer FA. Timing of food intake predicts weight loss effectiveness. Int J Obes (Lond). 2013;37:604–11.

    Article  CAS  Google Scholar 

  41. 41.

    Jakubowicz D, Barnea M, Wainstein J, Froy O. High caloric intake at breakfast vs. dinner differentially influences weight loss of overweight and obese women. Obesity (Silver Spring). 2013;21:2504–12.

    Article  CAS  Google Scholar 

  42. 42.

    Arble DM, Bass J, Laposky AD, Vitaterna MH, Turek FW. Circadian timing of food intake contributes to weight gain. Obesity (Silver Spring). 2009;17:2100–2.

    Article  Google Scholar 

  43. 43.

    Hairston KG, Bryer-Ash M, Norris JM, Haffner S, Bowden DW, Wagenknecht LE. Sleep duration and five-year abdominal fat accumulation in a minority cohort: the IRAS family study. Sleep. 2010;33:289–95.

    Article  PubMed  PubMed Central  Google Scholar 

  44. 44.

    Ardern CI, Katzmarzyk PT, Janssen I, Ross R. Discrimination of health risk by combined body mass index and waist circumference. Obes Res. 2003;11:135–42.

    Article  Google Scholar 

  45. 45.

    Janssen I, Katzmarzyk PT, Ross R. Waist circumference and not body mass index explains obesity-related health risk. Am J Clin Nutr. 2004;79:379–84.

    Article  CAS  Google Scholar 

  46. 46.

    Leproult R, Copinschi G, Buxton O, Van Cauter E. Sleep loss results in an elevation of cortisol levels the next evening. Sleep. 1997;20:865–70.

  47. 47.

    Donoho CJ, Weigensberg MJ, Emken BA, Hsu JW, Spruijt-Metz D. Stress and abdominal fat: preliminary evidence of moderation by the cortisol awakening response in Hispanic peripubertal girls. Obesity (Silver Spring). 2011;19:946–52.

    Article  Google Scholar 

  48. 48.

    Dashti HS, Zuurbier LA, de Jonge E, Voortman T, Jacques PF, Lamon-Fava S, et al. Actigraphic sleep fragmentation, efficiency and duration associate with dietary intake in the Rotterdam Study. J Sleep Res. 2016;25:404–11.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors especially thank the PREDIMED-Plus participants for their enthusiastic collaboration, the PREDIMED-Plus personnel for their outstanding support, and the personnel of all associated primary care centers for their exceptional effort. Centros de Investigación Biomédica en Red: Obesidad y Nutrición (CIBEROBN), Centros de Investigación Biomédica en Red: Epidemiología y Salud Pública (CIBERESP) and Centros de Investigación Biomédica en Red: Diabetes y Enfermedades Metabólicas asociadas (CIBERDEM) are initiatives of Instituto de Salud Carlos III (ISCIII), Madrid, Spain. Food companies, Hojiblanca and Patrimonio Comunal Olivarero, donated extra-virgin olive oil and Almond Board of California, American Pistachio Growers, and Paramount Farms donated nuts.

Funding

The PREDIMED-Plus trial was supported by the official funding agency for biomedical research of the Spanish government, ISCIII through the Fondo de Investigación para la Salud (FIS), which is co-funded by the European Regional Development Fund (three coordinated FIS projects led by JS-S and JV, including the following projects: PI13/00673, PI13/00492, PI13/00272, PI13/01123, PI13/00462, PI13/00233, PI13/02184, PI13/00728, PI13/01090, PI13/01056, PI14/01722, PI14/00636, PI14/00618, PI14/00696, PI14/01206, PI14/01919, PI14/00853, PI14/01374, PI16/00473, PI16/00662, PI16/01873, PI16/01094, PI16/00501, PI16/00533, PI16/00381, PI16/00366, PI16/01522, PI16/01120, PI17/00764, PI17/01183, PI17/00855, PI17/01347, PI17/00525, PI17/01827, PI17/00532, PI17/00215, PI17/01441, PI17/00508, PI17/01732, PI17/00926), the Especial Action Project entitled: Implementación y evaluación de una intervención intensiva sobre la actividad física Cohorte PREDIMED-PLUS grant to Jordi Salas-Salvadó, the European Research Council (Advanced Research Grant 2013–2018; 340918) grant to MÁM-G, the Recercaixa grant to JS-S (2013ACUP00194), the grant from the Consejería de Salud de la Junta de Andalucía (PI0458/2013; PS0358/2016), the PROMETEO/2017/017 grant from the Generalitat Valenciana, the SEMERGEN grant and FEDER funds (CB06/03), OC is granted by the JR17/00022, ISCIII. CP is supported by a postdoctoral fellowship granted by the Autonomous Government of Catalonia (PERIS 2016–2020 Incorporació de Científics i Tecnòlegs, SLT002/0016/00428). None of the funding sources took part in the design, collection, analysis or interpretation of the data, or in the decision to submit the manuscript for publication. The corresponding authors had full access to all the data in the study and had final responsibility to submit for publication.

Author contributions

CP, MB, and JS-S: designed the research. CP, MB, AD-L, MAM-G, DC, MF, JV, DR, JAM, JL-M, RE, AB-C, FA, JAT, FJT, LS-M, VM, JL, CV, XP, JV, LD, MD-R, ER, IA, JB-L, AG-A, NB, HS, ET, AA-G, and JS-S: conducted the research. CP, MB, and JS-S: analyzed the data. CP wrote the article. CP and JS-S are the guarantors of this work and, as such, had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. All authors revised the manuscript for important intellectual content and read and approved the final manuscript.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Jordi Salas-Salvadó.

Ethics declarations

Conflict of interest

JS-S reports serving on the board of and receiving grant support through his institution from International Nut and Dried Fruit Council; receiving consulting personal fees from Danone, Font Vella Lanjaron, Nuts for Life, and Eroski; and receiving grant support through his institution from Nut and Dried Fruit Foundation and Eroski. ER reports grants, non-financial support, and other fees from California Walnut Commission and Alexion; personal fees and non-financial support from Merck, Sharp & Dohme; personal fees, non-financial support, and other fees from Aegerion and Ferrer International; grants and personal fees from Sanofi Aventis; grants from Amgen and Pfizer and; personal fees from Akcea, outside of the submitted work. XP reports serving on the board of and receiving consulting personal fees from Sanofi Aventis, Amgen, and Abbott laboratories; receiving lecture personal fees from Esteve, Lacer, and Rubio laboratories. MD-R reports receiving grants from the Diputación Provincial de Jaén and the Caja Rural de Jaén. LD reports grants from Fundación Cerveza y Salud. The other authors declare that they have no conflict of interest.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Papandreou, C., Bulló, M., Díaz-López, A. et al. High sleep variability predicts a blunted weight loss response and short sleep duration a reduced decrease in waist circumference in the PREDIMED-Plus Trial. Int J Obes 44, 330–339 (2020). https://doi.org/10.1038/s41366-019-0401-5

Download citation

Further reading

Search