Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Epidemiology and population health

Day-to-day regularity in breakfast consumption is associated with weight status in a prospective cohort of women

Abstract

Background

Evidence suggests that regular eating patterns (i.e., consistent day-to-day frequency and timing of consumption) may be favorable with respect to weight status, and breakfast may be a particularly important meal for weight maintenance. We examined the relationship between regular breakfast consumption habits and weight status among women.

Materials and methods

Modified Poisson regression models examined day-to-day regularity in breakfast consumption among 46,037 women in the prospective Sister Study cohort in relation to weight status. Cross-sectional outcomes included overweight (body mass index (BMI) ≥ 25.0 kg/m2) and obesity (BMI ≥ 30.0 kg/m2); waist circumference (WC) ≥ 88 cm; and waist-to-hip ratio (WHR) ≥ 0.85. Self-reported weight 5 years post-baseline was used to calculate 5 kg weight gain and incident overweight and obesity using BMI.

Results

Compared to women who reported eating breakfast 3 to 4 days/week (irregular breakfast eaters), women who ate breakfast 7 days/week were between 11% to 17% less likely to be obese as measured by WHR (prevalence ratio (PR): 0.89; 95%CI: 0.85, 0.94), WC (PR: 0.85; 95%CI: 0.82, 0.88), and BMI (PR: 0.83; 95%CI: 0.79, 0.87) after multivariable adjustment. Women who never ate breakfast were between 11% to 22% less likely to be obese as measured by WHR (PR: 0.89; 95%CI: 0.83, 0.96), WC (PR: 0.82; 95%CI: 0.78, 0.87), and BMI (PR: 0.78; 95%CI: 0.72, 0.84) compared to irregular breakfast eaters. Prospective analyses showed a 21% and 28% lower risk of 5-year incident obesity among participants who always (relative risk (RR): 0.79; 95%CI: 0.70, 0.90) or never (RR: 0.72; 95%CI: 0.59, 0.87) ate breakfast, respectively, compared to those who ate breakfast 3 to 4 days/week. No association was observed for incident 5 kg weight gain.

Conclusions

Results suggest that a regular breakfast consumption habit, comprising eating breakfast every day or never, may be important for maintaining a healthy weight.

This is a preview of subscription content

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.

    St-Onge MP, Ard J, Baskin ML, Chiuve SE, Johnson HM, Kris-Etherton P, et al. Meal timing and frequency: implications for cardiovascular disease prevention: a scientific statement from the American Heart Association.Circulation. 2017;135:e96–e121.

    Article  Google Scholar 

  2. 2.

    American Diabetes Association. Postprandial blood glucose. American Diabetes Association. Diabetes Care. 2001;24:775–8.

    Article  Google Scholar 

  3. 3.

    Bennard P, Doucet E. Acute effects of exercise timing and breakfast meal glycemic index on exercise-induced fat oxidation. Appl Physiol Nutr Metab. 2006;31:502–11.

    CAS  Article  Google Scholar 

  4. 4.

    Betts JA, Richardson JD, Chowdhury EA, Holman GD, Tsintzas K, Thompson D. The causal role of breakfast in energy balance and health: a randomized controlled trial in lean adults. Am J Clin Nutr. 2014;100:539–47.

    CAS  Article  Google Scholar 

  5. 5.

    Chowdhury EA, Richardson JD, Holman GD, Tsintzas K, Thompson D, Betts JA. The causal role of breakfast in energy balance and health: a randomized controlled trial in obese adults. Am J Clin Nutr. 2016;103:747–56.

    CAS  Article  Google Scholar 

  6. 6.

    Johnston JD. Physiological responses to food intake throughout the day. Nutr Res Rev. 2014;27:107–18.

    CAS  Article  Google Scholar 

  7. 7.

    Oosterman JE, Kalsbeek A, la Fleur SE, Belsham DD. Impact of nutrients on circadian rhythmicity. Am J Phys Regul Integr Comp Physiol. 2015;308:R337–50.spring2

    CAS  Article  Google Scholar 

  8. 8.

    Kumar Jha P, Challet E, Kalsbeek A. Circadian rhythms in glucose and lipid metabolism in nocturnal and diurnal mammals. Mol Cell Endocr. 2015;418(Pt 1):74–88.

    CAS  Article  Google Scholar 

  9. 9.

    Depner CM, Stothard ER, Wright KP Jr.. Metabolic consequences of sleep and circadian disorders. Curr Diab Rep. 2014;14:507.

    Article  Google Scholar 

  10. 10.

    McHill AW, Wright KP Jr.. Role of sleep and circadian disruption on energy expenditure and in metabolic predisposition to human obesity and metabolic disease. Obes Rev. 2017;18(Suppl 1):15–24.

    Article  Google Scholar 

  11. 11.

    Hirao A, Nagahama H, Tsuboi T, Hirao M, Tahara Y, Shibata S. Combination of starvation interval and food volume determines the phase of liver circadian rhythm in Per2::Luc knock-in mice under two meals per day feeding. Am J Physiol Gastrointest Liver Physiol. 2010;299:G1045–53.

    CAS  Article  Google Scholar 

  12. 12.

    Scott EM, Carter AM, Grant PJ. Association between polymorphisms in the Clock gene, obesity and the metabolic syndrome in man. Int J Obes. 2008;32:658–62.

    CAS  Article  Google Scholar 

  13. 13.

    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.

    CAS  Article  Google Scholar 

  14. 14.

    Vieira E, Ruano E, Figueroa AL, Aranda G, Momblan D, Carmona F, et al. Altered clock gene expression in obese visceral adipose tissue is associated with metabolic syndrome. PloS ONE. 2014;9:e111678.

    Article  Google Scholar 

  15. 15.

    Song WO, Chun OK, Obayashi S, Cho S, Chung CE. Is consumption of breakfast associated with body mass index in US adults? J Am Diet Assoc. 2005;105:1373–82.

    Article  Google Scholar 

  16. 16.

    Sakurai M, Yoshita K, Nakamura K, Miura K, Takamura T, Nagasawa SY, et al. Skipping breakfast and 5-year changes in body mass index and waist circumference in Japanese men and women. Obes Sci Prac. 2017;3:162–70.

    CAS  Article  Google Scholar 

  17. 17.

    van der Heijden AA, Hu FB, Rimm EB, van Dam RM. A prospective study of breakfast consumption and weight gain among U.S. men. Obesity (Silver Spring). 2007;15:2463–9.

    Article  Google Scholar 

  18. 18.

    Ma Y, Bertone ER, Stanek EJ 3rd, Reed GW, Hebert JR, et al. Association between eating patterns and obesity in a free-living US adult population. Am J Epidemiol. 2003;158:85–92.

    Article  Google Scholar 

  19. 19.

    Watanabe Y, Saito I, Henmi I, Yoshimura K, Maruyama K, Yamauchi K, et al. Skipping breakfast is correlated with obesity. J Rural Med. 2014;9:51–8.

    Article  Google Scholar 

  20. 20.

    Deshmukh-Taskar P, Nicklas TA, Radcliffe JD, O’Neil CE, Liu Y. The relationship of breakfast skipping and type of breakfast consumed with overweight/obesity, abdominal obesity, other cardiometabolic risk factors and the metabolic syndrome in young adults. The National Health and Nutrition Examination Survey (NHANES): 1999–2006. Pub Health Nutr. 2013;16:2073–82.

    Article  Google Scholar 

  21. 21.

    Horikawa C, Kodama S, Yachi Y, Heianza Y, Hirasawa R, Ibe Y, et al. Skipping breakfast and prevalence of overweight and obesity in Asian and Pacific regions: a meta-analysis. Prev Med. 2011;53:260–7.

    Article  Google Scholar 

  22. 22.

    Sandler DP, Hodgson ME, Deming-Halverson SL, Juras PS, D’Aloisio AA, Suarez LM, et al. The Sister Study Cohort: baseline methods and participant characteristics. Environ Health Pespect. 2017;125:127003.

    Article  Google Scholar 

  23. 23.

    Block G, Hartman AM, Dresser CM, Carroll MD, Gannon J, Gardner L. A data-based approach to diet questionnaire design and testing. Am J Epidemol. 1986;124:453–69.

    CAS  Article  Google Scholar 

  24. 24.

    NHLBI Obesity Education Initiative Expert Panel on the Identification, Evaluation, and Treatment of Obesity in Adults (US). Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults—The Evidence Report. Report No.: 98-4083 (Bethesda, MD: National Heart, Lung, and Blood Institute; 1998).

  25. 25.

    World Health Organization. WHO Guidelines Approved by the Guidelines Review Committee. In: Global Recommendations on Physical Activity for Health. (Geneva: WHO, 2010).

  26. 26.

    Barros AJ, Hirakata VN. Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio. BMC Med Res Method. 2003;3:21.

    Article  Google Scholar 

  27. 27.

    Zou G. A modified poisson regression approach to prospective studies with binary data. Am J Eidemiology. 2004;159:702–6.

    Article  Google Scholar 

  28. 28.

    Krebs-Smith S, Pannucci T, Subar A, Kirkpatrick S, Lerman J, Tooze J. Update of the Healthy Eating Index: HEI-2015. J Acad Nutr Diet. 2018;118:1591–602.

    Article  Google Scholar 

  29. 29.

    Greenland S, Pearl J, Robins JM. Causal diagrams for epidemiologic research. Epidemiology. 1999;10:37–48.

    CAS  Article  Google Scholar 

  30. 30.

    Grundy SM. Multifactorial causation of obesity: implications for prevention. Am J Clin Nutr. 1998;67(3 Suppl):563s–72s.

    CAS  Article  Google Scholar 

  31. 31.

    Timlin MT, Pereira MA, Story M, Neumark-Sztainer D. Breakfast eating and weight change in a 5-year prospective analysis of adolescents: Project EAT (Eating Among Teens). Pediatrics. 2008;121:e638–45.

    Article  Google Scholar 

  32. 32.

    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. 2014;38:1159–64.

    CAS  Article  Google Scholar 

  33. 33.

    Spruyt K, Molfese DL, Gozal D. Sleep duration, sleep regularity, body weight, and metabolic homeostasis in school-aged children. Pediatrics. 2011;127:e345–52.

    Article  Google Scholar 

  34. 34.

    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;111:17302–7.

    CAS  Article  Google Scholar 

  35. 35.

    Thomas EA, Higgins J, Bessesen DH, McNair B, Cornier MA. Usual breakfast eating habits affect response to breakfast skipping in overweight women. Obesity (Silver Spring). 2015;23:750–9.

    Article  Google Scholar 

  36. 36.

    Burdge GC, Jones AE, Frye SM, Goodson L, Wootton SA. Effect of meal sequence on postprandial lipid, glucose and insulin responses in young men. Eur J Clin Nutr. 2003;57:1536–44.

    CAS  Article  Google Scholar 

  37. 37.

    Freedman LS, Commins JM, Moler JE, Arab L, Baer DJ, Kipnis V, et al. Pooled results from 5 validation studies of dietary self-report instruments using recovery biomarkers for energy and protein intake. Am J Epidemiol. 2014;180:172–88.

    Article  Google Scholar 

  38. 38.

    Rhee JJ, Sampson L, Cho E, Hughes MD, Hu FB, Willett WC. Comparison of methods to account for implausible reporting of energy intake in epidemiologic studies. Am J Epidemiol. 2015;181:225–33.

    Article  Google Scholar 

  39. 39.

    Lin CJ, DeRoo LA, Jacobs SR, Sandler DP. Accuracy and reliability of self-reported weight and height in the Sister Study. Public Health Nutr. 2012;15:989–99.

    Article  Google Scholar 

  40. 40.

    Spector D, Deroo LA, Sandler DP. Lifestyle behaviors in black and white women with a family history of breast cancer. Prev Med. 2011;52:394–7.

    Article  Google Scholar 

Download references

Acknowledgements

This work is supported in part by a grant from the National Institute of General Medical Sciences (T32-GM081740) to MAG and by the Intramural Research Program of the National Institutes of Health, the National Institute of Environmental Health Sciences (Z01-ES044005) to DPS. All authors contributed to the designed research, writing, and review of the manuscript. MAG conducted the analysis and DPS, the principal investigator of the Sister Study, provided access to the data. The authors appreciate the helpful comments of Drs. Katie M. O’Brien and Alexandra J. White.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Mark A. Guinter.

Ethics declarations

Conflict of interest

The 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

Guinter, M.A., Park, YM., Steck, S.E. et al. Day-to-day regularity in breakfast consumption is associated with weight status in a prospective cohort of women. Int J Obes 44, 186–194 (2020). https://doi.org/10.1038/s41366-019-0356-6

Download citation

Further reading

Search

Quick links