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Variability of Sleep and Relations to Body Weight Among First-Year College Students

  • Special Issue: Sleep Science
  • Published:
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Abstract

Background

Existing research suggests that greater sleep variability may increase risk for weight gain. College often marks a transition to a less consistent daily schedule, which may adversely impact sleep routines and further increase risk for weight gain. The current study is among the first to explore relations between nighttime sleep variability and daytime sleep (napping) and body weight among first-year college students.

Methods

Using daily diary methods, first-year college students (N = 307; 84.7% female) self-reported their sleep for seven days. Several indices were created to capture sleep variability for reported bedtime, wake time, and sleep duration, including weekday versus weekend differences (WvW), day to day differences (D2D), and overall standard deviation (SD). Napping was also assessed. Based on body mass index (BMI), individuals were categorized as underweight, healthy weight, overweight, and obese.

Results

Across indices, students’ sleep varied over an hour on average across the week. Hierarchical regressions revealed that greater differences in wake time D2D, wake time SD, and sleep duration WvW were all associated with higher BMI, after accounting for gender, depressive symptoms, and sleep duration. Longer napping was also associated with higher BMI, using the same covariates. Finally, greater sleep variability was reported by overweight and obese than healthy weight individuals.

Conclusion

These findings suggest that sleep variability, particularly wake times and napping may be important modifiable sleep behaviors to investigate in future studies. More longitudinal research is needed to explore relations between multiple facets of sleep variability and weight gain, including possible mechanisms.

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References

  1. Mokdad AH, Serdula MK, Dietz WH. The spread of the obesity epidemic in the United States, 1991-1998. JAMA. 1999;282:1519–22.

    CAS  PubMed  Google Scholar 

  2. Lloyd-Richardson EE, Bailey S, Fava JL. A prospective study of weight gain during the college freshman and sophomore years. Prev Med. 2009;48:256–61.

    PubMed  Google Scholar 

  3. Vella-Zarb RA, Elgar FJ. The ‘freshman 5’: a meta-analysis of weight gain in the freshman year of college. J Am Coll Heal. 2009;58:161–6.

    Google Scholar 

  4. Holm-Denoma JM, Joiner TE Jr, Vohs KD. The “freshman fifteen”(the “freshman five” actually): predictors and possible explanations. Health Psychol. 2008;27:S3–9.

    PubMed  Google Scholar 

  5. Vadeboncoeur C, Townsend N, Foster C. A meta-analysis of weight gain in first year university students: is freshman 15 a myth? BMC Obes. 2015;2(1):22.

    PubMed  PubMed Central  Google Scholar 

  6. Levitsky DA, Halbmaier CA, Mrdjenovic G. The freshman weight gain: a model for the study of the epidemic of obesity. Int J Obes Relat Metab Disord. 2004;28(11):1435–42.

    CAS  PubMed  Google Scholar 

  7. Mihalopoulos NL, Auinger P, Klein JD. The freshman 15: is it real? J Am Coll Heal. 2008;56(5):531–3.

    Google Scholar 

  8. Lund HG, Reider BD, Whiting AB. Sleep patterns and predictors of disturbed sleep in a large population of college students. J Adoles Health. 2010;46:124–32.

    Google Scholar 

  9. Doane LD, Gress-Smith JL, Breitenstein RS. Multi-method assessments of sleep over the transition to college and the associations with depression and anxiety symptoms. J Youth Adoles. 2015;44:389–404.

    Google Scholar 

  10. Patel SR, Hu FB. Short sleep duration and weight gain: a systematic review. Obesity. 2008;16:643–53.

    PubMed  Google Scholar 

  11. Chen X, Beydoun MA, Wang Y. Is sleep duration associated with childhood obesity? A systematic review and meta-analysis. Obesity. 2008;16:265–74.

    PubMed  Google Scholar 

  12. Fatima Y, Doi SA, Mamun AA. Longitudinal impact of sleep on overweight and obesity in children and adolescents: a systematic review and bias-adjusted meta-analysis. Obes Rev. 2015;16:137–49.

    CAS  PubMed  Google Scholar 

  13. Guidolin M, Gradisar M. Is shortened sleep duration a risk factor for overweight and obesity during adolescence? A review of the empirical literature. Sleep Med. 2012;13:779–86.

    PubMed  Google Scholar 

  14. Chaput JP, Sjödin AM, Astrup A. Risk factors for adult overweight and obesity: the importance of looking beyond the ‘big two’. Obes Facts. 2010;3:320–7.

    PubMed  PubMed Central  Google Scholar 

  15. Bei B, Wiley JF, Trinder J. Beyond the mean: a systematic review on the correlates of daily intraindividual variability of sleep/wake patterns. Sleep Med Rev. 2016;28:108–24.

    PubMed  Google Scholar 

  16. Becker SP, Sidol CA, Van Dyk TR. Intraindividual variability of sleep/wake patterns in relation to child and adolescent functioning: a systematic review. Sleep Med Rev. 2017;34:94–121.

    PubMed  Google Scholar 

  17. Dills AK, Hernandez-Julian R. Course scheduling and academic performance. Econom Educ Rev. 2008;27:646–54.

    Google Scholar 

  18. Vela-Bueno A, Fernandez-Mendoza J, Olavarrieta-Bernardino S, Vgontzas AN, Bixler EO, de la Cruz-Troca JJ, et al. Sleep and behavioral correlates of napping among young adults: a survey of first-year university students in Madrid, Spain. J Am Coll Health. 2008;57:150–8.

    PubMed  Google Scholar 

  19. Whiting WL, Murdock KK. Emerging adults’ sleep patterns and attentional capture: the pivotal role of consistency. Cog Processing. 2016;17:155–62.

    Google Scholar 

  20. Bailey BW, Allen MD, LeCheminant JD, et al. Objectively measured sleep patterns in young adult women and the relationship to adiposity. Am J of H Promot. 2014;29:46–54.

    Google Scholar 

  21. Chan WS. Delay discounting and response disinhibition moderate associations between actigraphically measured sleep parameters and body mass index. J Sleep Res. 2017;26:21–9.

    PubMed  Google Scholar 

  22. Roane BM, Seifer R, Sharkey KM, van Reen E, Bond TLY, Raffray T, et al. What role does sleep play in weight gain in the first semester of university? Behav Sleep Med. 2015;13:491–505.

    PubMed  Google Scholar 

  23. Parsons MJ, Moffitt TE, Gregory AM, Goldman-Mellor S, Nolan PM, Poulton R, et al. Social jetlag, obesity and metabolic disorder: investigation in a cohort study. Int J Obes. 2015;39:842–8.

    CAS  Google Scholar 

  24. Rutters F, Lemmens SG, Adam TC, Bremmer MA, Elders PJ, Nijpels G, et al. Is social jetlag associated with an adverse endocrine, behavioral, and cardiovascular risk profile? J Biol Rhythm. 2014;29:377–83.

    Google Scholar 

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

    CAS  PubMed  Google Scholar 

  26. Ye L, Hutton Johnson S, Keane K. Napping in college students and its relationship with nighttime sleep. J Am Coll Heal. 2015;63:88–97.

    Google Scholar 

  27. Lovato N, Lack L, Wright H. The napping behaviour of australian university students. PloS one. 2014;9:e113666.

    PubMed  PubMed Central  Google Scholar 

  28. Gradisar M, Wright H, Robinson J. Adolescent napping behavior: comparisons of school week versus weekend sleep patterns. Sleep Biol Rhythms. 2008;6:183–6.

    Google Scholar 

  29. Devine JK, Wolf JM. Integrating nap and night-time sleep into sleep patterns reveals differential links to health-relevant outcomes. J Sleep Res. 2016;25(2):225–33.

    PubMed  Google Scholar 

  30. Patel SR, Hayes AL, Blackwell T, et al. The association between sleep patterns and obesity in older adults. Int J of Obes. 2014;38:1159–64.

    CAS  Google Scholar 

  31. Bayon V, Leger D, Gomez-Merino D. Sleep debt and obesity. Ann of Med. 2014;46:264–72.

    Google Scholar 

  32. American Psychiatric Association. Diagnostic and statistical manual of mental disorders (DSM-5®). American Psychiatric Pub. 2013.

  33. Barefoot JC, Heitmann BL, Helms MJ, et al. Symptoms of depression and changes in body weight from adolescence to mid-life. Int J Obes. 1998;7:688–94.

    Google Scholar 

  34. World Health Organization. WHO Expert Committee on Physical Status: the use and interpretation of anthropometry. Geneva: World Health Organization; 1995. WHO Technical Report Series;854.

  35. Quick V, Byrd-Bredbenner C, Shoff S, White AA, Lohse B, Horacek T, et al. Concordance of self-report and measured height and weight of college students. J Nutr Educ Behav. 2015;47:94–8.

    PubMed  Google Scholar 

  36. Andresen EM, Malmgren JA, Carter WB, Patrick DL. Screening for depression in well older adults: evaluation of a short form of the CES-D. Am J Prev Med. 1994;10:77–84.

    CAS  PubMed  Google Scholar 

  37. Bradley KL, Bagnell AL, Brannen CL. Factorial validity of the Center for Epidemiological Studies Depression 10 in adolescents. Issues Ment Health Nurs. 2010;31:408–12.

    PubMed  Google Scholar 

  38. Hirshkowitz M, Whiton K, Albert SM. National Sleep Foundation’s updated sleep duration recommendations. Sleep Health. 2015;1:233–43.

    PubMed  Google Scholar 

  39. Suh S, Nowakowski S, Bernert RA, Ong JC, Siebern AT, Dowdle CL, et al. Clinical significance of night-to-night sleep variability in insomnia. Sleep Med. 2012;13:469–75.

    PubMed  PubMed Central  Google Scholar 

  40. Jahng S, Wood PK, Trull TJ. Analysis of affective instability in ecological momentary assessment: indices using successive difference and group comparison via multilevel modeling. Psychol Methods. 2008;13:354–75.

    PubMed  Google Scholar 

  41. Sánchez-Ortuño MM, Carney CE, Edinger JD. Moving beyond average values: assessing the night-to-night instability of sleep and arousal in DSM-IV-TR insomnia subtypes. Sleep. 2011;34:531–9.

    PubMed  PubMed Central  Google Scholar 

  42. Russell CJ, Dean MA. To log or not to log: bootstrap as an alternative to the parametric estimation of moderation effects in the presence of skewed dependent variables. Org Res Methods. 2000;3:166–85.

    Google Scholar 

  43. Fletcher D, MacKenzie D, Villouta E. Modelling skewed data with many zeros: a simple approach combining ordinary and logistic regression. Environ and Ecolog Stats. 2005;12:45–54.

    Google Scholar 

  44. Rascati KL, Smith MJ, Neilands T. Dealing with skewed data: an example using asthma-related costs of medicaid clients. Clin Therapeutics. 2001;23:481–98.

    CAS  Google Scholar 

  45. Sainani KL. Dealing with non-normal data. PM&R. 2012;4:1001–5.

    Google Scholar 

  46. Field AP, Wilcox RR. Robust statistical methods: a primer for clinical psychology and experimental psychopathology researchers. Beh Res & Ther. 2017;98:19–38.

    Google Scholar 

  47. Moore M, Kirchner HL, Drotar D. Correlates of adolescent sleep time and variability in sleep time: the role of individual and health related characteristics. Sleep Med. 2011;12:239–45.

    PubMed  PubMed Central  Google Scholar 

  48. Wittmann M, Dinich J, Merrow M. Social jetlag: misalignment of biological and social time. Chronobiol Int. 2006;23:497–509.

    PubMed  Google Scholar 

  49. Westerterp-Plantenga MS. Sleep, circadian rhythm and body weight: parallel developments. Proc Nutr Soc. 2016;75:431–9.

    CAS  PubMed  Google Scholar 

  50. Beebe DW, Lewin D, Zeller M, McCabe M, MacLeod K, Daniels SR, et al. Sleep in overweight adolescents: shorter sleep, poorer sleep quality, sleepiness, and sleep-disordered breathing. J Ped Psy. 2007;32:69–79.

    Google Scholar 

  51. Regestein QR, Friebely J, Shifren JL, Scharf MB, Wiita B, Carver J, et al. Self-reported sleep in postmenopausal women. Menopause. 2004;11:198–207.

    PubMed  Google Scholar 

  52. Phillips AJ, Clerx WM, O’Brien CS, et al. Irregular sleep/wake patterns are associated with poorer academic performance and delayed circadian and sleep/wake timing. Sci Reports. 2017;7:3216.

    Google Scholar 

  53. Barker DH, Phillips AJ, Carskadon MA. Evaluation of the Sleep Regularity Index (SRI) among first-year college students: association with alcohol use, caffeine consumption, academic load, and negative mood. Age. 2017;57:598.

    Google Scholar 

  54. Galland B, Meredith-Jones K, Terrill P. Challenges and emerging technologies within the field of pediatric actigraphy. Front Psychiatry. 2014;5:99.

    PubMed  PubMed Central  Google Scholar 

  55. Thacher PV. University students and the “All Nighter”: correlates and patterns of students’ engagement in a single night of total sleep deprivation. Beh Sleep Med. 2008;6:16–31.

    Google Scholar 

  56. Hedeker D, Mermelstein RJ, Demirtas H. An application of a mixed-effects location scale model for analysis of ecological momentary assessment (EMA) data. Biometrics. 2008;64:627–34.

    PubMed  Google Scholar 

  57. Wang LP, Hamaker E, Bergeman CS. Investigating inter-individual differences in short-term intra-individual variability. Psychol Methods. 2012;17:567–81.

    PubMed  Google Scholar 

  58. He F, Bixler EO, Berg A, Imamura Kawasawa Y, Vgontzas AN, Fernandez-Mendoza J, et al. Habitual sleep variability, not sleep duration, is associated with caloric intake in adolescents. Sleep Med. 2015;16:856–61.

    PubMed  Google Scholar 

  59. 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.

    PubMed  PubMed Central  Google Scholar 

  60. Kjeldsen JS, Hjorth MF, Andersen R, Michaelsen KF, Tetens I, Astrup A, et al. Short sleep duration and large variability in sleep duration are independently associated with dietary risk factors for obesity in Danish school children. Int J Obes. 2014;38:32–9.

    CAS  Google Scholar 

  61. Racette SB, Weiss EP, Schechtman KB. Influence of weekend lifestyle patterns on body weight. Obesity. 2008;16:1826–30.

    PubMed  Google Scholar 

  62. Daugherty JR, Brase GL. Taking time to be healthy: predicting health behaviors with delay discounting and time perspective. Pers Individ Differ. 2010;48:202–7.

    Google Scholar 

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Acknowledgements

This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. 1842190. Dr. Moreno is supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development of the National Institutes of Health under award number K99HD091396 and the United States Department of Agriculture (USDA/ARS) under Cooperative Agreement No. 58-3092-5-001.

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Authors and Affiliations

  1. Loyola University Chicago, Chicago, USA

    Laura M. Nicholson, Amy H. Egbert & Amy M. Bohnert

  2. USDA/ARS Children’s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA

    Jennette P. Moreno

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  1. Laura M. Nicholson
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  2. Amy H. Egbert
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Correspondence to Laura M. Nicholson.

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Nicholson, L.M., Egbert, A.H., Moreno, J.P. et al. Variability of Sleep and Relations to Body Weight Among First-Year College Students. Int.J. Behav. Med. 28, 227–237 (2021). https://doi.org/10.1007/s12529-020-09888-3

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