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Epidemiology and Population Health

Circadian timing of eating and BMI among adults in the American Time Use Survey

International Journal of Obesity volume 46, pages 287–296 (2022)Cite this article

Subjects

Abstract

Background/objectives

Experimental studies of time-restricted eating suggest that limiting the daily eating window, shifting intake to the biological morning, and avoiding eating close to the biological night may promote metabolic health and prevent weight gain.

Subjects/methods

We used the Eating & Health Module of the 2006–2008 and 2014–2016 American Time Use Survey to examine cross-sectional associations of timing of eating in relation to sleep/wake times as a proxy for circadian timing with body mass index (BMI). The analytical sample included 38 302 respondents (18–64 years; BMI 18.5–50.0 kg/m2). A single 24-hour time use diary was used to calculate circadian timing of eating variables: eating window (time between first and last eating activity); morning fast (time between end of sleep and start of eating window); and evening fast (time between end of eating window and start of sleep). Multinomial logistic regression and predictive margins were used to estimate adjusted population prevalences (AP) by BMI categories and changes in prevalences associated with a one-hour change in circadian timing of eating, controlling for sociodemographic and temporal characteristics.

Results

A one-hour increase in eating window was associated with lower adjusted prevalence of obesity (AP = 27.1%, SE = 0.1%). Conversely, a one-hour increase in morning fast (AP = 28.7%, SE = 0.1%) and evening fast (AP = 28.5%, SE = 0.1%) were each associated with higher prevalence of obesity; interactions revealed differing patterns of association by combination of eating window with morning/evening fast (p < 0.0001).

Conclusions

Contrary to hypotheses, longer eating windows were associated with a lower adjusted prevalence of obesity and longer evening fasts were associated with a higher prevalence of obesity. However, as expected, longer morning fast was associated with a higher adjusted prevalence of obesity. Studies are needed to disentangle the contributions of diet quality/quantity and social desirability bias in the relationship between circadian timing of eating and BMI.

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Fig. 1: Illustration of circadian timing of eating variables from two hypothetical days in the American Time Use Survey Eating and Health Module (ATUS-EHM), from 4:00 on Day 1 to 3:59 on Day 2.
Fig. 2: Population-adjusted mean, standard deviation, and range of circadian timing of eating characteristics by BMI category among N = 38 302 respondents from the American Time Use Survey Eating and Health Module (ATUS-EHM).

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References

  1. Chaix A, Manoogian ENC, Melkani GC, Panda S. Time-restricted eating to prevent and manage chronic metabolic diseases. Annu Rev Nutr. 2019;39:291–315.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Wilkinson MJ, Manoogian ENC, Zadourian A, Lo H, Fakhouri S, Shoghi A, et al. Ten-hour time-restricted eating reduces weight, blood pressure, and atherogenic lipids in patients with metabolic syndrome. Cell Metab. 2020;31:92–104 e5.

    Article  CAS  PubMed  Google Scholar 

  3. Moon S, Kang J, Kim SH, Chung HS, Kim YJ, Yu JM, et al. Beneficial effects of time-restricted eating on metabolic diseases: a systemic review and meta-analysis. Nutrients. 2020;12:1267.

    Article  PubMed Central  Google Scholar 

  4. Swiatkiewicz I, Wozniak A, Taub PR. Time-restricted eating and metabolic syndrome: current status and future perspectives. Nutrients. 2021;13:221.

    Article  PubMed  PubMed Central  Google Scholar 

  5. 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  PubMed  PubMed Central  Google Scholar 

  6. Paoli A, Tinsley G, Bianco A, Moro T. The influence of meal frequency and timing on health in humans: the role of fasting. Nutrients. 2019;11:719.

    Article  PubMed Central  Google Scholar 

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

    Article  PubMed  Google Scholar 

  8. Kahleova H, Lloren JI, Mashchak A, Hill M, Fraser GE. Meal frequency and timing are associated with changes in body mass index in adventist health study 2. J Nutr. 2017;147:1722–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Xiao Q, Garaulet M, Scheer F. Meal timing and obesity: interactions with macronutrient intake and chronotype. Int J Obes. 2019;43:1701–11.

    Article  Google Scholar 

  10. Roenneberg T, Kuehnle T, Juda M, Kantermann T, Allebrandt K, Gordijn M, et al. Epidemiology of the human circadian clock. Sleep Med Rev. 2007;11:429–38.

    Article  PubMed  Google Scholar 

  11. Fischer D, Lombardi DA, Marucci-Wellman H, Roenneberg T. Chronotypes in the US–Influence of age and sex. PLoS One. 2017;12:e0178782.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Innominato PF, Roche VP, Palesh OG, Ulusakarya A, Spiegel D, Levi FA. The circadian timing system in clinical oncology. Ann Med. 2014;46:191–207.

    Article  CAS  PubMed  Google Scholar 

  13. Patterson RE, Sears DD. Metabolic effects of intermittent fasting. Annu Rev Nutr. 2017;37:371–93.

    Article  CAS  PubMed  Google Scholar 

  14. Zarrinpar A, Chaix A, Panda S. Daily eating patterns and their impact on health and disease. Trends Endocrinol Metab. 2016;27:69–83.

    Article  CAS  PubMed  Google Scholar 

  15. de Cabo R, Mattson MP. Effects of intermittent fasting on health, aging, and disease. N Engl J Med. 2019;381:2541–51.

    Article  PubMed  Google Scholar 

  16. Gill S, Panda S. A smartphone app reveals erratic diurnal eating patterns in humans that can be modulated for health benefits. Cell Metab. 2015;22:789–98.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Oike H, Oishi K, Kobori M. Nutrients, clock genes, and chrononutrition. Curr Nutr Rep. 2014;3:204–12.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Aoyama S, Shibata S. Time-of-day-dependent physiological responses to meal and exercise. Front Nutr. 2020;7:18.

    Article  PubMed  PubMed Central  Google Scholar 

  19. 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. 2013;21:2504–12.

    Article  CAS  PubMed  Google Scholar 

  20. Gu C, Brereton N, Schweitzer A, Cotter M, Duan D, Borsheim E, et al. Metabolic effects of late dinner in healthy volunteers–a randomized crossover clinical trial. J Clin Endocrinol Metab. 2020;105:2789–2802.

    Article  PubMed Central  Google Scholar 

  21. Al-Naimi S, Hampton SM, Richard P, Tzung C, Morgan LM. Postprandial metabolic profiles following meals and snacks eaten during simulated night and day shift work. Chronobiology International. 2009;21:937–47.

    Article  Google Scholar 

  22. Okada C, Imano H, Muraki I, Yamada K, Iso H. The association of having a late dinner or bedtime snack and skipping breakfast with overweight in japanese women. J Obes. 2019;2019:2439571.

    Article  PubMed  PubMed Central  Google Scholar 

  23. McHill AW, Phillips AJ, Czeisler CA, Keating L, Yee K, Barger LK, et al. Later circadian timing of food intake is associated with increased body fat. Am J Clin Nutr. 2017;106:1213–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Hutchison AT, Regmi P, Manoogian ENC, Fleischer JG, Wittert GA, Panda S, et al. Time-restricted feeding improves glucose tolerance in men at risk for type 2 diabetes: a randomized crossover trial. Obesity (Silver Spring). 2019;27:724–32.

    CAS  Google Scholar 

  25. Jamshed H, Beyl RA, Della Manna DL, Yang ES, Ravussin E, Peterson CM. Early time-restricted feeding improves 24-hour glucose levels and affects markers of the circadian clock, aging, and autophagy in humans. Nutrients. 2019;11:1234.

    Article  PubMed Central  Google Scholar 

  26. Cienfuegos S, Gabel K, Kalam F, Ezpeleta M, Wiseman E, Pavlou V, et al. Effects of 4- and 6-h time-restricted feeding on weight and cardiometabolic health: a randomized controlled trial in adults with obesity. Cell Metab. 2020;32:366–378.e3.

    Article  CAS  PubMed  Google Scholar 

  27. Pellegrini M, Cioffi I, Evangelista A, Ponzo V, Goitre I, Ciccone G, et al. Effects of time-restricted feeding on body weight and metabolism. A systematic review and meta-analysis. Rev Endocr Metab Disord. 2020;21:17–33.

    Article  PubMed  Google Scholar 

  28. Czeisler CA, Weitzman E, Moore-Ede MC, Zimmerman JC, Knauer RS. Human sleep: its duration and organization depend on its circadian phase. Science. 1980;210:1264–7.

    Article  CAS  PubMed  Google Scholar 

  29. Sletten TL, Vincenzi S, Redman JR, Lockley SW, Rajaratnam SM. Timing of sleep and its relationship with the endogenous melatonin rhythm. Front Neurol. 2010;1:137.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Lovato N, Micic G, Gradisar M, Ferguson SA, Burgess HJ, Kennaway DJ, et al. Can the circadian phase be estimated from self-reported sleep timing in patients with Delayed Sleep Wake Phase Disorder to guide timing of chronobiologic treatment? Chronobiol Int. 2016;33:1376–90.

    Article  CAS  PubMed  Google Scholar 

  31. American Time Use Survey User’s Guide 2020 https://www.bls.gov/tus/atususersguide.pdf.

  32. American Time Use Survey Data Extract Builder: Version 2.7 [dataset] [Internet]. https://doi.org/10.18128/D060.V2.7.

  33. Zeballos E, Todd JE, Restrepo B. Frequency and time of day that Americans eat: a comparison of frequency and time of day data from the American Data From the American Time Use Survey and the National Health and Nutrition Examination Survey. US Department of Agriculture. 2019; Economic Research Service.

  34. Obesity: preventing and managing the global epidemic. Report of a WHO consultation. World Health Organization Technical Report Series 2000.

  35. Skeldon AC, Derks G, Dijk DJ. Modelling changes in sleep timing and duration across the lifespan: changes in circadian rhythmicity or sleep homeostasis? Sleep Med Rev. 2016;28:96–107.

    Article  PubMed  Google Scholar 

  36. Korn E, Graubard B. Epidemiologic studies utilizing surveys: accounting for the sampling design. Am J Public Health. 1991;81:1166–73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Chow LS, Manoogian ENC, Alvear A, Fleischer JG, Thor H, Dietsche K, et al. Time-restricted eating effects on body composition and metabolic measures in humans who are overweight: a feasibility study. Obesity (Silver Spring). 2020;28:860–9.

    Article  CAS  Google Scholar 

  38. Adafer R, Messaadi W, Meddahi M, Patey A, Haderbache A, Bayen S, et al. Food timing, circadian rhythm and chrononutrition: a systematic review of time-restricted eating’s effects on human health. Nutrients. 2020;12:3770.

    Article  PubMed Central  Google Scholar 

  39. Lean ME, Malkova D. Altered gut and adipose tissue hormones in overweight and obese individuals: cause or consequence? Int J Obes. 2016;40:622–32.

    Article  CAS  Google Scholar 

  40. Kesztyus D, Cermak P, Gulich M, Kesztyus T. Adherence to time-restricted feeding and impact on abdominal obesity in primary care patients: results of a pilot study in a pre-post design. Nutrients. 2019;11:2854

    Article  PubMed Central  Google Scholar 

  41. 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  PubMed  PubMed Central  Google Scholar 

  42. Wing RR, Phelan S. Long-term weight loss maintenance. Am J Clin Nutr. 2005;82:222S–225S.

    Article  CAS  PubMed  Google Scholar 

  43. Bonnet JP, Cardel MI, Cellini J, Hu FB, Guasch-Ferre M. Breakfast skipping, body composition, and cardiometabolic risk: a systematic review and meta-analysis of randomized trials. Obesity. 2020;28:1098–1109.

    Article  CAS  PubMed  Google Scholar 

  44. Dashti HS, Scheer F, Saxena R, Garaulet M. Timing of food intake: identifying contributing factors to design effective interventions. Adv Nutr. 2019;10:606–20.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Leech RM, Worsley A, Timperio A, McNaughton SA. Understanding meal patterns: definitions, methodology and impact on nutrient intake and diet quality. Nutr Res Rev. 2015;28:1–21.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Matthews CE, Berrigan D, Fischer B, Gomersall SR, Hillreiner A, Kim Y, et al. Use of previous-day recalls of physical activity and sedentary behavior in epidemiologic studies: results from four instruments. BMC Public Health. 2019;19:478.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Matthews CE, Keadle SK, Sampson J, Lyden K, Bowles HR, Moore SC, et al. Validation of a previous-day recall measure of active and sedentary behaviors. Med Sci Sports Exerc. 2013;45:1629–38.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Harms T, Gershuny J, Doherty A, Thomas E, Milton K, Foster C. A validation study of the Eurostat harmonised European time use study (HETUS) diary using wearable technology. BMC Public Health. 2019;19:455.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Ekelund U, Brage S, Besson H, Sharp S, Wareham NJ. Time spent being sedentary and weight gain in healthy adults: reverse or bidirectional causality? Am J Clin Nutr. 2008;88:612–7.

    Article  CAS  PubMed  Google Scholar 

  50. Carroll RJ, Ruppert D, Stefanski LA, Crainiceanu CM. Measurement error in nonlinear models: a modern perspective, second edition: CRC Press; 2006. 455 p.

  51. Kaplan RL, Kopp B, Phipps P. Contrasting stylized questions of sleep with diary measures from the American Time Use Survey. Office of Survey Methods Research, Bureau of Labor Statistics; 2016.

  52. Jakubowicz D, Froy O, Wainstein J, Boaz M. Meal timing and composition influence ghrelin levels, appetite scores and weight loss maintenance in overweight and obese adults. Steroids. 2012;77:323–31.

    Article  CAS  PubMed  Google Scholar 

  53. Teixeira GP, Barreto ACF, Mota MC, Crispim CA. Caloric midpoint is associated with total calorie and macronutrient intake and body mass index in undergraduate students. Chronobiol Int. 2019;36:1418–28.

    Article  CAS  PubMed  Google Scholar 

  54. Bo S, Musso G, Beccuti G, Fadda M, Fedele D, Gambino R, et al. Consuming more of daily caloric intake at dinner predisposes to obesity. A 6-year population-based prospective cohort study. PLoS One. 2014;9:e108467.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Kant AK. Eating patterns of US adults: meals, snacks, and time of eating. Physiol Behav. 2018;193:270–8.

    Article  CAS  PubMed  Google Scholar 

  56. Kant AK, Graubard BI. 40-year trends in meal and snack eating behaviors of American adults. J Acad Nutr Diet. 2015;115:50–63.

    Article  PubMed  Google Scholar 

  57. Goris AH, Westerterp-Plantenga MS, Westerterp KR. Undereating and underrecording of habitual food intake in obese men: selective underreporting of fat intake. Am J Clin Nutr. 2000;71:130–4.

    Article  CAS  PubMed  Google Scholar 

  58. Macdiarmid J, Blundell J. Assessing dietary intake: who, what and why of under-reporting. Nutr Res Rev. 1998;11:231–53.

    Article  CAS  PubMed  Google Scholar 

  59. Scientific Report of the 2020 Dietary Guidelines Advisory Committee: Advisory Report to the Secretary of Agriculture and the Secretary of Health and Human Services. Washington, DC: U.S. Department of Agriculture, Agricultural Research Service; 2020.

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Authors and Affiliations

  1. Health Behaviors Research Branch, Behavioral Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA

    Sydney G. O’Connor, Susan M. Czajkowski & David Berrigan

  2. Risk Factor Assessment Branch, Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA

    Jill Reedy

  3. Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA

    Barry I. Graubard

  4. Department of Family, Nutrition, and Exercise Sciences, Queens College, The City University of New York, New York, NY, USA

    Ashima K. Kant

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Contributions

SGO designed the study, led the statistical analysis, and drafted the manuscript. AKK, JR, and SMC contributed to the interpretation of results and critically revised the manuscript. BIG contributed to the statistical analysis and interpretation of results, and critically revised manuscript. DB contributed to the analytical design, statistical analysis, and interpretation, and critically revised the manuscript.

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Correspondence to Sydney G. O’Connor.

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O’Connor, S.G., Reedy, J., Graubard, B.I. et al. Circadian timing of eating and BMI among adults in the American Time Use Survey. Int J Obes 46, 287–296 (2022). https://doi.org/10.1038/s41366-021-00983-3

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