Skip to main content

Advertisement

SpringerLink
Log in

Integration of Time-Based Recommendations with Current Pediatric Health Behavior Guidelines: Implications for Obesity Prevention and Treatment in Youth

  • Childhood Obesity (A Kelly and C Fox, Section Editors)
  • Published:
Current Obesity Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

Youth-onset obesity is associated with negative health outcomes across the lifespan including cardiovascular diseases, type 2 diabetes, obstructive sleep apnea, dyslipidemias, asthma, and several cancers. Pediatric health guidelines have traditionally focused on the quality and quantity of dietary intake, physical activity, and sleep.

Recent Findings

Emerging evidence suggests that the timing (time of day when behavior occurs) and composition (proportion of time spent allocated to behavior) of food intake, movement (i.e., physical activity, sedentary time), and sleep may independently predict health trajectories and disease risks. Several theoretically driven interventions and conceptual frameworks feature behavior timing and composition (e.g., 24 h movement continuum, circadian science and chronobiology, intermittent fasting regimens, structured day hypothesis). These literatures are, however, disparate, with little crosstalk across disciplines. In this review, we examine dietary, sleep, and movement guidelines and recommendations for youths ages 0–18 in the context of theoretical models and empirical findings in support of time-based approaches.

Summary

The review aims to inform a unifying framework of health behaviors and guide future research on the integration of time-based recommendations into current quantity and quality-based health guidelines for children and adolescents.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. •• Hart CN, Jelalian E, Raynor HA. Behavioral and social routines and biological rhythms in prevention and treatment of pediatric obesity. Am Psychol. 2020;75(2):152–62. This review highlights the importance of integrating nutrition, activity, and sleep across the lifespan to promote health and revent pediatric obesity.

  2. Copeland KC, et al. Characteristics of adolescents and youth with recent-onset type 2 diabetes: the TODAY cohort at baseline. J Clin Endocrinol Metab. 2011;96(1):159–67.

    Article  CAS  Google Scholar 

  3. Marcus MD, et al. Weight change in the management of youth-onset type 2 diabetes: the TODAY clinical trial experience. Pediatr Obes. 2017;12(4):337–45.

    Article  CAS  Google Scholar 

  4. Narasimhan S, Weinstock RS. Youth-onset type 2 diabetes mellitus: lessons learned from the TODAY study. Mayo Clin Proc. 2014;89(6):806–16.

    Article  Google Scholar 

  5. Ogden CL, et al. Trends in obesity prevalence by race and hispanic origin-1999-2000 to 2017–2018. JAMA. 2020;324(12):1208–10.

    Article  Google Scholar 

  6. Hart CN, et al. Effect of changes in children’s bedtime and sleep period on targeted eating behaviors and timing of caloric intake. Eat Behav. 2022;45:101629.

    Article  Google Scholar 

  7. Spaeth AM, et al. Sleep, energy balance, and meal timing in school-aged children. Sleep Med. 2019;60:139–44.

    Article  Google Scholar 

  8. Tryggestad JB, Willi SM. Complications and comorbidities of T2DM in adolescents: findings from the TODAY clinical trial. J Diabetes Complications. 2015;29(2):307–12.

    Article  Google Scholar 

  9. Carson V, et al. Systematic review of the relationships between physical activity and health indicators in the early years (0–4 years). BMC Public Health. 2017;17(Suppl 5):854.

    Article  Google Scholar 

  10. Tremblay MS, Carson V, Chaput JP. Introduction to the Canadian 24 hour Movement Guidelines for Children and Youth: an integration of physical activity, sedentary behaviour, and sleep. Appl Physiol Nutr Metab. 2016;41(6 Suppl 3):iii–iv.

    Article  Google Scholar 

  11. Tremblay MS, et al. Canadian 24 hour Movement Guidelines for Children and Youth: an integration of physical activity, sedentary behaviour, and sleep. Appl Physiol Nutr Metab. 2016;41(6 Suppl 3):S311–27.

    Article  Google Scholar 

  12. Chaput J-P, et al. Importance of all movement behaviors in a 24 hour period for overall health. Int J Environ Res Public Health. 2014;11(12):12575–81.

    Article  Google Scholar 

  13. Tremblay M, et al. Physiological and health implications of a sedentary lifestyle. Appl Physiol Nutr Metab. 2010;35(6):725–40.

    Article  Google Scholar 

  14. World Health Organization. Guidelines on physical activity, sedentary behaviour and sleep for children under 5 years of age. World Health Organization; 2019.

    Google Scholar 

  15. Brazendale K, et al. Understanding differences between summer vs. school obesogenic behaviors of children: the structured days hypothesis. Int J Behav Nutr Phys Act. 2017;14(1):100.

    Article  Google Scholar 

  16. World Health Organization. Guiding principles for feeding non-breastfed children 6–24 months of age. World Health Organization; 2005.

    Google Scholar 

  17. American Academy of Pediatrics, Altmann T, Hill DL. Caring for your baby and young child: birth to age 5. 7th ed. Bantam Books; 2019.

    Book  Google Scholar 

  18. Meek JY, Noble L. Section on Breastfeeding. Policy Statement: Breastfeeding and the Use of Human Milk. Pediatrics. 2022 Jul 1;150(1):e2022057988. https://doi.org/10.1542/peds.2022-057988. PMID: 35921640

  19. Langley-Evans SC. Complementary feeding: Should baby be leading the way? J Hum Nutr Diet. 2022 Apr;35(2):247–249. https://doi.org/10.1111/jhn.12988. Epub 2022 Jan 23. PMID: 35066946; PMCID: PMC9303566.

  20. Ainsworth MDS, et al. Patterns of attachment: a psychological study of the strange situation. Hillsdale, NJ: Lawrence Erlbaum Assoc; 1978.

    Google Scholar 

  21. Bugenthal DB, Goodnow JJ. Socialization processes. In: Damon W, Eisenberg N, editors. Handbook of child psychology. 5th ed. New York, NY: Wiley; 1998. p. 389–462.

    Google Scholar 

  22. Bronfenbrenner U, Ceci SJ. Nature-nurture reconceptualized in developmental perspective: a bioecological model. Psychol Rev. 1994;101(4):568–86.

    Article  CAS  Google Scholar 

  23. Sameroff A. A unified theory of development: a dialectic integration of nature and nurture. Child Dev. 2010;81(1):6–22.

    Article  Google Scholar 

  24. Sameroff AJ. Environmental context of child development. J Pediatr. 1986;109(1):192–200.

    Article  CAS  Google Scholar 

  25. Sameroff AJ. Systems, development, and early intervention. Monogr Soc Res Child Dev. 1992;57(6):154–63.

    Article  CAS  Google Scholar 

  26. McNally J, et al. Communicating hunger and satiation in the first 2 years of life: a systematic review. Matern Child Nutr. 2016;12(2):205–28.

  27. •• Schneider-Worthington CR, et al. Learning to overeat in infancy: concurrent and prospective relationships between maternal BMI, feeding practices and child eating response among Hispanic mothers and children. Pediatr Obes. 2021;16(6):e12756. Maternal characteristics both biological and behavioral are associated with feeding practices and weight trajectory in Hispanic youth.

  28. Power TG, et al. Observations of maternal feeding practices and styles and young children’s obesity risk: a longitudinal study of Hispanic mothers with low incomes. Child Obes. 2021;17(1):16–25.

    Article  Google Scholar 

  29. Hughes SO, et al. Maternal feeding style and child weight status among Hispanic families with low-income levels: a longitudinal study of the direction of effects. Int J Behav Nutr Phys Act. 2021;18(1):30.

    Article  Google Scholar 

  30. Papaioannou MA, et al. Maternal feeding styles and child appetitive traits: direction of effects in Hispanic families with low incomes. Front Public Health. 2022;10:871923.

    Article  Google Scholar 

  31. Vaughn AE, et al. Fundamental constructs in food parenting practices: a content map to guide future research. Nutr Rev. 2016;74(2):98–117.

    Article  Google Scholar 

  32. Rivkees SA, Mirmiran M, Ariagno RL. Circadian Rhythms in Infants. Neoreviews. 2003;4:e298–e304.

  33. Mirmiran M, Ariagno RL. Influence of light in the NICU on the development of circadian rhythms in preterm infants. Semin Perinatol. 2000;24(4):247–57.

    Article  CAS  Google Scholar 

  34. Seron-Ferre M, et al. The development of circadian rhythms in the fetus and neonate. Semin Perinatol. 2001;25(6):363–70.

    Article  CAS  Google Scholar 

  35. Escobar C, Rojas-Granados A, Angeles-Castellanos M. Development of the circadian system and relevance of periodic signals for neonatal development. Handb Clin Neurol. 2021;179:249–58.

    Article  Google Scholar 

  36. Lohr B, Siegmund R. Ultradian and circadian rhythms of sleep-wake and food-intake behavior during early infancy. Chronobiol Int. 1999;16(2):129–48.

    Article  CAS  Google Scholar 

  37. Italianer MF, et al. Circadian variation in human milk composition, a systematic review. Nutrients. 2020;12(8):2328.

    Article  CAS  Google Scholar 

  38. Gombert M, Codoner-Franch P. Melatonin in early nutrition: long-term effects on cardiovascular system. Int J Mol Sci. 2021;22(13):6809.

    Article  CAS  Google Scholar 

  39. Qin Y, et al. Variations in melatonin levels in preterm and term human breast milk during the first month after delivery. Sci Rep. 2019;9(1):17984.

    Article  Google Scholar 

  40. Cubero J, et al. The circadian rhythm of tryptophan in breast milk affects the rhythms of 6-sulfatoxymelatonin and sleep in newborn. Neuro Endocrinol Lett. 2005;26(6):657–61.

    CAS  Google Scholar 

  41. Rivkees SA, et al. Rest-activity patterns of premature infants are regulated by cycled lighting. Pediatrics. 2004;113(4):833–9.

    Article  Google Scholar 

  42. Mann NP, et al. Effect of night and day on preterm infants in a newborn nursery: randomised trial. Br Med J Clin Res Ed. 1986;293(6557):1265–7.

    Article  CAS  Google Scholar 

  43. Black MM, et al. Early childhood development coming of age: science through the life course. Lancet. 2017;389(10064):77–90.

    Article  Google Scholar 

  44. Hewitt L, et al. Tummy time and infant health outcomes: a systematic review. Pediatrics. 2020;145(6):e20192168.

    Article  Google Scholar 

  45. US Department of Agriculture, US Department of Health and Human Services. Dietary Guidelines for Americans, 2020–2025. 9th ed. 2020.

  46. Luque V, et al. Unhealthy dietary patterns established in infancy track to mid-childhood: the EU Childhood Obesity Project. J Nutr. 2018;148(5):752–9.

    Article  Google Scholar 

  47. Lioret S, et al. Dietary patterns track from infancy to preschool age: cross-sectional and longitudinal perspectives. J Nutr. 2015;145(4):775–82.

    Article  CAS  Google Scholar 

  48. Mikkila V, et al. Consistent dietary patterns identified from childhood to adulthood: the cardiovascular risk in Young Finns Study. Br J Nutr. 2005;93(6):923–31.

    Article  CAS  Google Scholar 

  49. Walton K, et al. Time to re-think picky eating?: a relational approach to understanding picky eating. Int J Behav Nutr Phys Act. 2017;14(1):62.

    Article  Google Scholar 

  50. Centers for Disease Control and Prevention - National Center for Health Statistics. Clinical Growth Charts. https://www.cdc.gov/growthcharts/clinical_charts.htm. Cited 10 May 2022.

  51. Haynes PL, Gengler D, Kelly M. Social rhythm therapies for mood disorders: an update. Curr Psychiatry Rep. 2016;18(8):1–8.

    Article  Google Scholar 

  52. Pliner P, Salvy SJ. Food neophobia in humans. In: Shepherd R, Raats M, editors. Psychology of Food Choice. CABI Publishing; 2006.

    Google Scholar 

  53. Taylor CM, et al. Picky/fussy eating in children: review of definitions, assessment, prevalence and dietary intakes. Appetite. 2015;95:349–59.

    Article  Google Scholar 

  54. Charvet A, et al. Impact of eating frequency and snack quality on body weight of WIC preschool children. Curr Dev Nutr. 2020;4:1616.

    Article  Google Scholar 

  55. Taylor R, et al. Eating frequency in relation to BMI in very young children: a longitudinal analysis. Public Health Nutr. 2017;20:1372–9.

    Article  Google Scholar 

  56. Syrad H, et al. Meal size is a critical driver of weight gain in early childhood. Sci Rep. 2016;6:28368.

    Article  CAS  Google Scholar 

  57. Eng S, Wagstaff DA, Kranz S. Eating late in the evening is associated with childhood obesity in some age groups but not in all children: the relationship between time of consumption and body weight status in U.S. children. Int J Behav Nutr Phys Act. 2009;6:27.

    Article  Google Scholar 

  58. • Goetz AR, et al. The role of sleep and eating patterns in adiposity gain among preschool-aged children. Am J Clin Nutr. 2022. Sleep timing and relationship to food frequency and consumption is associated with adipsoity trajectory and gain in preschool-aged children.

  59. Tremblay MS, et al. Canadian 24 hour Movement Guidelines for the Early Years (0–4 years): an integration of physical activity, sedentary behaviour, and sleep. BMC Public Health. 2017;17(Suppl 5):874.

    Article  Google Scholar 

  60. Australian Government Department of Health and Aged Care. Physical activity and exercise guidelines for all Australians. https://www.health.gov.au/health-topics/physical-activity-and-exercise/physical-activity-and-exercise-guidelines-for-all-australians?utm_source=health.gov.au&utm_medium=callout-auto-custom&utm_campaign=digital_transformation. Cited 20 Jun 2022.

  61. Chastin SF, et al. Combined effects of time spent in physical activity, sedentary behaviors and sleep on obesity and cardio-metabolic health markers: a novel compositional data analysis approach. PLoS ONE. 2015;10(10):e0139984.

    Article  Google Scholar 

  62. Clarke AE, et al. Meeting Canadian 24 hour Movement Guideline recommendations and risk of all-cause mortality. Appl Physiol Nutr Metab. 2021;46(12):1487–94.

    Article  Google Scholar 

  63. Clarke AE, Janssen I. A compositional analysis of time spent in sleep, sedentary behaviour and physical activity with all-cause mortality risk. Int J Behav Nutr Phys Act. 2021;18(1):25.

    Article  Google Scholar 

  64. Butte NF, et al. Role of physical activity and sleep duration in growth and body composition of preschool-aged children. Obesity. 2016;24(6):1328–35.

    Article  Google Scholar 

  65. Chaput JP, et al. Systematic review of the relationships between sleep duration and health indicators in the early years (0–4 years). BMC Public Health. 2017;17(Suppl 5):855.

    Article  Google Scholar 

  66. Miller MA, et al. Systematic review and meta-analyses of the relationship between short sleep and incidence of obesity and effectiveness of sleep interventions on weight gain in preschool children. Obes Rev. 2021;22(2):e13113.

    Article  Google Scholar 

  67. Wang F, et al. Sleep duration and overweight/obesity in preschool-aged children: a prospective study of up to 48,922 children of the Jiaxing Birth Cohort. Sleep. 2016;39(11):2013–9.

    Article  Google Scholar 

  68. Bruce ES, Lunt L, McDonagh JE. Sleep in adolescents and young adults. Clin Med. 2017;17(5):424–8.

    Article  Google Scholar 

  69. Reyna-Vargas ME, et al. Longitudinal associations between sleep habits, screen time and overweight, obesity in preschool children. Nat Sci Sleep. 2022;14:1237–47.

    Article  Google Scholar 

  70. Hart CN, et al. Changes in children’s sleep duration on food intake, weight, and leptin. Pediatrics. 2013;132(6):e1473–80.

    Article  Google Scholar 

  71. Hart CN, et al. Effect of experimental change in children’s sleep duration on television viewing and physical activity. Pediatr Obes. 2017;12(6):462–7.

    Article  CAS  Google Scholar 

  72. Goncalves WSF, et al. Parental influences on screen time and weight status among preschool children from Brazil: a cross-sectional study. Int J Behav Nutr Phys Act. 2019;16(1):27.

    Article  Google Scholar 

  73. Pate RR, et al. Physical activity and health in children younger than 6 years: a systematic review. Med Sci Sports Exerc. 2019;51(6):1282–91.

    Article  Google Scholar 

  74. Poitras VJ, et al. Systematic review of the relationships between sedentary behaviour and health indicators in the early years (0–4 years). BMC Public Health. 2017;17(Suppl 5):868.

    Article  Google Scholar 

  75. Veldman SLC, Chin APMJM, Altenburg TM. Physical activity and prospective associations with indicators of health and development in children aged < 5 years: a systematic review. Int J Behav Nutr Phys Act. 2021;18(1):6.

    Article  Google Scholar 

  76. Carson V, Tremblay MS, Chastin SFM. Cross-sectional associations between sleep duration, sedentary time, physical activity, and adiposity indicators among Canadian preschool-aged children using compositional analyses. BMC Public Health. 2017;17(Suppl 5):848.

    Article  Google Scholar 

  77. Cliff DP, et al. Adherence to 24 hour Movement Guidelines for the Early Years and associations with social-cognitive development among Australian preschool children. BMC Public Health. 2017;17(Suppl 5):857.

    Article  Google Scholar 

  78. Taylor RW, et al. Adherence to 24 h movement behavior guidelines and psychosocial functioning in young children: a longitudinal analysis. Int J Behav Nutr Phys Act. 2021;18(1):110.

    Article  Google Scholar 

  79. Guan H, et al. Proportion of kindergarten children meeting the WHO guidelines on physical activity, sedentary behaviour and sleep and associations with adiposity in urban Beijing. BMC Pediatr. 2020;20(1):70.

    Article  Google Scholar 

  80. Akacem LD, Wright KP, LeBourgeois MK. Bedtime and evening light exposure influence circadian timing in preschool-age children: a field study. Neurobiol Sleep Circadian Rhythms. 2016;1(2):27–31.

    Article  Google Scholar 

  81. Yokomaku A, et al. A study of the association between sleep habits and problematic behaviors in preschool children. Chronobiol Int. 2008;25(4):549–64.

    Article  Google Scholar 

  82. Nicklas T, Johnson R, American Dietetic Association. Position of the American Dietetic Association: dietary guidance for healthy children ages 2 to 11 years. J Am Diet Assoc. 2004;104(4):660–77.

    Article  Google Scholar 

  83. Wang Y, et al. What childhood obesity prevention programmes work? A systematic review and meta-analysis. Obes Rev. 2015;16(7):547–65.

    Article  CAS  Google Scholar 

  84. Phillips JA. Dietary Guidelines for Americans, 2020–2025. Workplace Health Saf. 2021;69(8):395.

    Article  Google Scholar 

  85. Annan RA, et al. Relationship between breakfast consumption, BMI status and physical fitness of Ghanaian school-aged children. BMC Nutr. 2020;6:19.

    Article  Google Scholar 

  86. Bonnet JP, et al. Breakfast skipping, body composition, and cardiometabolic risk: a systematic review and meta-analysis of randomized trials. Obesity. 2020;28(6):1098–109.

    Article  CAS  Google Scholar 

  87. Blondin SA, et al. Breakfast consumption and adiposity among children and adolescents: an updated review of the literature. Pediatr Obes. 2016;11(5):333–48.

    Article  CAS  Google Scholar 

  88. Jeans MR, et al. Breakfast consumption in low-income Hispanic elementary school-aged children: associations with anthropometric, metabolic, and dietary parameters. Nutrients. 2020;12(7):2038.

    Article  Google Scholar 

  89. You Y, et al. Breakfast preferences and consumption location among children at a median age of 7 in Shenzhen: implications for managing overweight and obesity. Appetite. 2021;156:104851.

    Article  Google Scholar 

  90. Berg C, et al. Eating patterns and portion size associated with obesity in a Swedish population. Appetite. 2009;52(1):21–6.

    Article  Google Scholar 

  91. Berteus Forslund H, et al. Meal patterns and obesity in Swedish women-a simple instrument describing usual meal types, frequency and temporal distribution. Eur J Clin Nutr. 2002;56(8):740–7.

    Article  CAS  Google Scholar 

  92. Bo S, 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(9):e108467.

    Article  Google Scholar 

  93. O’Connor S, et al. Temporal eating patterns and weight status among US adults in the American Time Use Survey (ATUS). Curr Dev Nutr. 2020;4(Supplement_2):592.

    Article  Google Scholar 

  94. St-Onge MP, et al. Meal timing and frequency: implications for cardiovascular disease prevention: a scientific statement from the American Heart Association. Circulation. 2017;135(9):e96–121.

    Article  Google Scholar 

  95. Wang J, et al. Timing of energy intake during the day is associated with the risk of obesity in adults. J Hum Nutr Diet. 2014;27:255–62.

    Article  Google Scholar 

  96. Thompson OM, et al. Dietary pattern as a predictor of change in BMI z-score among girls. Int J Obes. 2006;30(1):176–82.

    Article  CAS  Google Scholar 

  97. Evans EW, et al. The role of eating frequency on relative weight in urban school-age children. Pediatr Obes. 2015;10(6):442–7.

    Article  CAS  Google Scholar 

  98. Koletzko B, Toschke AM. Meal patterns and frequencies: do they affect body weight in children and adolescents? Crit Rev Food Sci Nutr. 2010;50(2):100–5.

    Article  Google Scholar 

  99. Mesas AE, et al. Selected eating behaviours and excess body weight: a systematic review. Obes Rev. 2012;13(2):106–35.

    Article  CAS  Google Scholar 

  100. Macdiarmid J, et al. Meal and snacking patterns of school-aged children in Scotland. Eur J Clin Nutr. 2009;63(11):1297–304.

    Article  CAS  Google Scholar 

  101. Murakami K, Livingstone MB. Associations of eating frequency with adiposity measures, blood lipid profiles and blood pressure in British children and adolescents. Br J Nutr. 2014;111(12):2176–83.

    Article  CAS  Google Scholar 

  102. Nicklas TA, et al. Children’s meal patterns have changed over a 21-year period: the Bogalusa Heart Study. J Am Diet Assoc. 2004;104(5):753–61.

    Article  Google Scholar 

  103. Panagiotakos DB, et al. Breakfast cereal is associated with a lower prevalence of obesity among 10–12-year-old children: the PANACEA study. Nutr Metab Cardiovasc Dis. 2008;18(9):606–12.

    Article  Google Scholar 

  104. Antonogeorgos G, et al. Breakfast consumption and meal frequency interaction with childhood obesity. Pediatr Obes. 2012;7(1):65–72.

    Article  CAS  Google Scholar 

  105. Huang TT, et al. Energy intake and meal portions: associations with BMI percentile in U.S. children. Obes Res. 2004;12(11):1875–85.

    Article  Google Scholar 

  106. Kaisari P, Yannakoulia M, Panagiotakos DB. Eating frequency and overweight and obesity in children and adolescents: a meta-analysis. Pediatrics. 2013;131(5):958–67.

    Article  Google Scholar 

  107. Popkin BM, Duffey KJ. Does hunger and satiety drive eating anymore? Increasing eating occasions and decreasing time between eating occasions in the United States. Am J Clin Nutr. 2010;91(5):1342–7.

    Article  CAS  Google Scholar 

  108. Roßbach S, et al. Age and time trends in eating frequency and duration of nightly fasting of German children and adolescents. Eur J Nutr. 2017;56(8):2507–17.

    Article  Google Scholar 

  109. Byars KC, Simon SL. American Academy of Pediatrics 2016 Safe Sleep Practices: implications for pediatric behavioral sleep medicine. Behav Sleep Med. 2017;15(3):175–9.

    Article  Google Scholar 

  110. Arteaga SS, et al. Childhood obesity research at the NIH: efforts, gaps, and opportunities. Transl Behav Med. 2018;8(6):962–7.

    Article  Google Scholar 

  111. Benjamin EJ, et al. Heart Disease and Stroke Statistics-2019 Update: a report from the American Heart Association. Circulation. 2019;139(10):e56–528.

    Article  Google Scholar 

  112. Chaput JP, et al. Systematic review of the relationships between sleep duration and health indicators in school-aged children and youth. Appl Physiol Nutr Metab. 2016;41(6 Suppl 3):S266–82.

    Article  Google Scholar 

  113. Phillips R. Late to bed, late to rise, could be cardiometabolically unwise. Nat Rev Endocrinol. 2016;12(1):1–1.

    Article  Google Scholar 

  114. Narang I, et al. Sleep disturbance and cardiovascular risk in adolescents. CMAJ. 2012;184(17):E913–20.

    Article  Google Scholar 

  115. Taylor BJ, et al. Bedtime variability and metabolic health in midlife women: the SWAN sleep study. Sleep. 2016;39(2):457–65.

    Article  Google Scholar 

  116. Knutson KL, et al. Association between sleep timing, obesity, diabetes: the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) Cohort Study. Sleep. 2017;40(4):zsx014.

    Article  Google Scholar 

  117. Huang T, Redline S. Cross-sectional and prospective associations of actigraphy-assessed sleep regularity with metabolic abnormalities: the multi-ethnic study of atherosclerosis. Diabetes Care. 2019;42(8):1422–9.

    Article  CAS  Google Scholar 

  118. Dutil C, et al. Sleep timing and health indicators in children and adolescents: a systematic review. Health Promot Chronic Dis Prev Can. 2022;42(4):150–69.

    Article  Google Scholar 

  119. Katzmarzyk PT, et al. Sedentary behavior and health: update from the 2018 Physical Activity Guidelines Advisory Committee. Med Sci Sports Exerc. 2019;51(6):1227–41.

    Article  Google Scholar 

  120. Piercy KL, et al. The physical activity guidelines for Americans. JAMA. 2018;320(19):2020–8.

    Article  Google Scholar 

  121. Dempsey PC, et al. New global guidelines on sedentary behaviour and health for adults: broadening the behavioural targets. Int J Behav Nutr Phys Act. 2020;17(1):151.

    Article  Google Scholar 

  122. Rosenberger ME, et al. The 24 hour Activity Cycle: a new paradigm for physical activity. Med Sci Sports Exerc. 2019;51(3):454–64.

    Article  Google Scholar 

  123. Janssen I, Roberts KC, Thompson W. Is adherence to the Canadian 24 hour Movement Behaviour Guidelines for Children and Youth associated with improved indicators of physical, mental, and social health? Appl Physiol Nutr Metab. 2017;42(7):725–31.

    Article  Google Scholar 

  124. Chen ST, et al. Meeting 24 h movement guidelines: prevalence, correlates, and the relationships with overweight and obesity among Chinese children and adolescents. J Sport Health Sci. 2021;10(3):349–59.

    Article  Google Scholar 

  125. Xiong X, et al. Association between 24 hour movement behaviors and health-related quality of life in children. Qual Life Res. 2022;31(1):231–40.

    Article  Google Scholar 

  126. Yerramalla MS, et al. Association of daily composition of physical activity and sedentary behaviour with incidence of cardiovascular disease in older adults. Int J Behav Nutr Phys Act. 2021;18(1):83.

    Article  Google Scholar 

  127. Gupta N, et al. Is daily composition of movement behaviors related to blood pressure in working adults? Med Sci Sports Exerc. 2018;50(10):2150–5.

    Article  Google Scholar 

  128. McGregor DE, et al. Differences in physical activity time-use composition associated with cardiometabolic risks. Prev Med Rep. 2019;13:23–9.

    Article  CAS  Google Scholar 

  129. Rollo S, et al. Health associations with meeting the Canadian 24 hour movement guidelines for adults: results from the Canadian Health Measures Survey. Health Rep. 2022;33(1):16–26.

    Google Scholar 

  130. Lucas-de la Cruz L, et al. Movement behaviors and cardiometabolic risk in schoolchildren. PLoS One. 2018;13(11):e0207300.

    Article  Google Scholar 

  131. Schumacher LM, et al. Sustaining regular exercise during weight loss maintenance: the role of consistent exercise timing. J Phys Act Health. 2021;18(10):1253–60.

    Article  Google Scholar 

  132. Chomistek AK, Shiroma EJ, Lee IM. The relationship between time of day of physical activity and obesity in older women. J Phys Act Health. 2016;13(4):416–8.

    Article  Google Scholar 

  133. Fullick S, et al. Prior exercise lowers blood pressure during simulated night-work with different meal schedules. Am J Hypertens. 2009;22(8):835–41.

    Article  Google Scholar 

  134. Fullick S, et al. Relationships between leisure-time energy expenditure and individual coping strategies for shift-work. Ergonomics. 2009;52(4):448–55.

    Article  CAS  Google Scholar 

  135. Baranowski T, et al. School year versus summer differences in child weight gain: a narrative review. Child Obes. 2014;10(1):18–24.

    Article  Google Scholar 

  136. Duncan S, et al. Efficacy of a compulsory homework programme for increasing physical activity and healthy eating in children: the healthy homework pilot study. Int J Behav Nutr Phys Act. 2011;8:127.

    Article  Google Scholar 

  137. Jago R, et al. Cross-sectional associations between the screen-time of parents and young children: differences by parent and child gender and day of the week. Int J Behav Nutr Phys Act. 2014;11:54.

    Article  Google Scholar 

  138. Olds T, Ridley K, Dollman J. Screenieboppers and extreme screenies: the place of screen time in the time budgets of 10–13 year-old Australian children. Aust N Z J Public Health. 2006;30(2):137–42.

    Article  Google Scholar 

  139. Olds T, Maher C, Dumuid D. Life on holidays: differences in activity composition between school and holiday periods in Australian children. BMC Public Health. 2019;19(Suppl 2):450.

    Article  Google Scholar 

  140. Rothausen BW, et al. Differences in Danish children’s diet quality on weekdays v. weekend days. Public Health Nutr. 2012;15(9):1653–60.

    Article  Google Scholar 

  141. Sanders T, et al. The influence of neighbourhood green space on children’s physical activity and screen time: findings from the longitudinal study of Australian children. Int J Behav Nutr Phys Act. 2015;12:126.

    Article  Google Scholar 

  142. Svensson A, et al. European children’s sugar intake on weekdays versus weekends: the IDEFICS study. Eur J Clin Nutr. 2014;68(7):822–8.

    Article  CAS  Google Scholar 

  143. Tanskey LA, et al. The state of the summer: a review of child summer weight gain and efforts to prevent it. Curr Obes Rep. 2018;7(2):112–21.

    Article  Google Scholar 

  144. Vissers PA, et al. Breakfast consumption and daily physical activity in 9–10-year-old British children. Public Health Nutr. 2013;16(7):1281–90.

    Article  Google Scholar 

  145. Sanders LM, et al. Implementing the 2020–2025 Dietary Guidelines for Americans: Recommendations for a Path Forward. Curr Dev Nutr. 2021;5(12):nzab136.

    Article  Google Scholar 

  146. Storz MA, Ronco AL. Nutrient intake in low-carbohydrate diets in comparison to the 2020–2025 Dietary Guidelines for Americans: a cross-sectional study. Br J Nutr. 2022;1–14.

  147. Krebs-Smith SM, et al. Update of the Healthy Eating Index: HEI-2015. J Acad Nutr Diet. 2018;118(9):1591–602.

    Article  Google Scholar 

  148. Norris SA, et al. Nutrition in adolescent growth and development. Lancet. 2022;399(10320):172–84.

    Article  Google Scholar 

  149. Reedy J, et al. Evaluation of the Healthy Eating Index-2015. J Acad Nutr Diet. 2018;118(9):1622–33.

    Article  Google Scholar 

  150. Karimi G, et al. Healthy eating index in a nationally representative sample of children and adolescents by socio-demographic characteristics: the weight disorders survey of the CASPIAN-IV study. Turk J Pediatr. 2020;62(6):930–9.

    Article  Google Scholar 

  151. Vinyard M, et al. Healthy Eating Index-2015 scores vary by types of food outlets in the United States. Nutrients. 2021;13(8):2717.

    Article  CAS  Google Scholar 

  152. Fanti M, et al. Time-restricted eating, intermittent fasting, and fasting-mimicking diets in weight loss. Curr Obes Rep. 2021;10(2):70–80.

    Article  Google Scholar 

  153. Adafer R, et al. Food timing, circadian rhythm and chrononutrition: a systematic review of time-restricted eating’s effects on human health. Nutrients. 2020;12(12):3770.

    Article  Google Scholar 

  154. Vidmar AP, et al. Timing of food consumption in Hispanic adolescents with obesity. Pediatr Obes. 2021;16(7):e12764.

    Article  Google Scholar 

  155. Williams KV, et al. The effect of short periods of caloric restriction on weight loss and glycemic control in type 2 diabetes. Diabetes Care. 1998;21(1):2–8.

    Article  CAS  Google Scholar 

  156. Antoni R, et al. Intermittent v. continuous energy restriction: differential effects on postprandial glucose and lipid metabolism following matched weight loss in overweight/obese participants. Br J Nutr. 2018;119(5):507–16.

    Article  CAS  Google Scholar 

  157. Carter S, Clifton PM, Keogh JB. The effects of intermittent compared to continuous energy restriction on glycaemic control in type 2 diabetes; a pragmatic pilot trial. Diabetes Res Clin Pract. 2016;122:106–12.

    Article  CAS  Google Scholar 

  158. Charlot A, et al. Beneficial effects of early time-restricted feeding on metabolic diseases: importance of aligning food habits with the circadian clock. Nutrients. 2021;13(5):1405.

    Article  CAS  Google Scholar 

  159. Harvie MN, et al. The effects of intermittent or continuous energy restriction on weight loss and metabolic disease risk markers: a randomized trial in young overweight women. Int J Obes. 2011;35(5):714–27.

    Article  CAS  Google Scholar 

  160. Harvie M, et al. The effect of intermittent energy and carbohydrate restriction v. daily energy restriction on weight loss and metabolic disease risk markers in overweight women. Br J Nutr. 2013;110(8):1534–47.

    Article  CAS  Google Scholar 

  161. Harvie MN, et al. Intermittent energy restriction induces changes in breast gene expression and systemic metabolism. Breast Cancer Res. 2016;18(1):57.

    Article  Google Scholar 

  162. Heilbronn LK, et al. Alternate-day fasting in nonobese subjects: effects on body weight, body composition, and energy metabolism. Am J Clin Nutr. 2005;81(1):69–73.

    Article  CAS  Google Scholar 

  163. Hoddy KK, et al. Meal timing during alternate day fasting: impact on body weight and cardiovascular disease risk in obese adults. Obesity. 2014;22(12):2524–31.

    Article  CAS  Google Scholar 

  164. Keogh JB, et al. Effects of intermittent compared to continuous energy restriction on short-term weight loss and long-term weight loss maintenance. Clin Obes. 2014;4(3):150–6.

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  166. Sundfor TM, Tonstad S, Svendsen M. Effects of intermittent versus continuous energy restriction for weight loss on diet quality and eating behavior. A randomized trial. Eur J Clin Nutr. 2019;73(7):1006–14.

    Article  CAS  Google Scholar 

  167. Varady KA, et al. Short-term modified alternate-day fasting: a novel dietary strategy for weight loss and cardioprotection in obese adults. Am J Clin Nutr. 2009;90(5):1138–43.

    Article  CAS  Google Scholar 

  168. Hatori M, et al. Time-restricted feeding without reducing caloric intake prevents metabolic diseases in mice fed a high-fat diet. Cell Metab. 2012;15(6):848–60.

    Article  CAS  Google Scholar 

  169. Belkacemi L, et al. Intermittent fasting modulation of the diabetic syndrome in streptozotocin-injected rats. Int J Endocrinol. 2012;2012:962012.

    Article  Google Scholar 

  170. Chaix A, et al. Time-restricted feeding prevents obesity and metabolic syndrome in mice lacking a circadian clock. Cell Metab. 2019;29(2):303–19.

    Article  CAS  Google Scholar 

  171. Chaix A, et al. Time-restricted feeding is a preventative and therapeutic intervention against diverse nutritional challenges. Cell Metab. 2014;20(6):991–1005.

    Article  CAS  Google Scholar 

  172. Jamshed H, et al. Effectiveness of early time-restricted eating for weight loss, fat loss, and cardiometabolic health in adults with obesity: a randomized clinical trial. JAMA. 2022;182(9):953–62.

    Google Scholar 

  173. Poggiogalle E, Jamshed H, Peterson CM. Circadian regulation of glucose, lipid, and energy metabolism in humans. Metabolism. 2018;84:11–27.

    Article  CAS  Google Scholar 

  174. Turbitt WJ, et al. Therapeutic time-restricted feeding reduces renal tumor bioluminescence in mice but fails to improve Anti-CTLA-4 efficacy. Anticancer Res. 2020;40(10):5445–56.

    Article  CAS  Google Scholar 

  175. Jamshed H, et al. Early time-restricted feeding improves 24 hour glucose levels and affects markers of the circadian clock, aging, and autophagy in humans. Nutrients. 2019;11(6):1234.

    Article  CAS  Google Scholar 

  176. Sutton EF, et al. Early time-restricted feeding improves insulin sensitivity, blood pressure, and oxidative stress even without weight loss in men with prediabetes. Cell Metab. 2018;27(6):1212–21.

    Article  CAS  Google Scholar 

  177. Lobene AJ, et al. Time-restricted eating for 12 weeks does not adversely alter bone turnover in overweight adults. Nutrients. 2021;13(4):1155.

    Article  CAS  Google Scholar 

  178. Crose A, et al. Time-restricted eating improves quality of life measures in overweight humans. Nutrients. 2021;13(5):1430.

    Article  Google Scholar 

  179. Malaeb S, et al. Time-restricted eating alters food intake patterns, as prospectively documented by a smartphone application. Nutrients. 2020;12(11):3396.

    Article  Google Scholar 

  180. Chow LS, et al. Time-restricted eating effects on body composition and metabolic measures in humans who are overweight: a feasibility study. Obesity. 2020;28(5):860–9.

    Article  CAS  Google Scholar 

  181. Bandin C, et al. Meal timing affects glucose tolerance, substrate oxidation and circadian-related variables: a randomized, crossover trial. Int J Obes. 2015;39(5):828–33.

    Article  CAS  Google Scholar 

  182. Panda S. Circadian physiology of metabolism. Science. 2016;354(6315):1008–15.

    Article  CAS  Google Scholar 

  183. Morris CJ, et al. Effects of the internal circadian system and circadian misalignment on glucose tolerance in chronic shift workers. J Clin Endocrinol Metab. 2016;101(3):1066–74.

    Article  CAS  Google Scholar 

  184. Pan X, et al. Circadian clock, time-restricted feeding and reproduction. Int J Mol Sci. 2020;21(3):831.

    Article  CAS  Google Scholar 

  185. Cespedes Feliciano EM, et al. Chronotype, social jet lag, and cardiometabolic risk factors in early adolescence. JAMA Pediatr. 2019;173(11):1049–57.

    Article  Google Scholar 

  186. Regmi P, et al. Early or delayed time-restricted feeding prevents metabolic impact of obesity in mice. J Endocrinol. 2021;248(1):75–86.

    Article  CAS  Google Scholar 

  187. Varady KA, et al. Cardiometabolic benefits of intermittent fasting. Annu Rev Nutr. 2021;41:333–61.

    Article  Google Scholar 

  188. Hagenauer MH, Lee TM. The neuroendocrine control of the circadian system: adolescent chronotype. Front Neuroendocrinol. 2012;33(3):211–29.

    Article  CAS  Google Scholar 

  189. Almoosawi S, et al. Chronotype: implications for epidemiologic studies on chrono-nutrition and cardiometabolic health. Adv Nutr. 2019;10(1):30–42.

    Article  Google Scholar 

  190. •• Vidmar AP, et al. Time-limited eating and continuous glucose monitoring in adolescents with obesity: a pilot study. Nutrients. 2021;13(11):3697. There is a growing interest in investigating the use of time restricted eating in individuals with obesity. This is the first sudy to investigate the use of an 8 h time restricted eating intervention in adolescents with obesity.

  191. Vidmar AP, et al. Time limited eating in adolescents with obesity (time LEAd): study protocol. Contemp Clin Trials. 2020;95:106082.

    Article  Google Scholar 

  192. Naguib MN, et al. Continuous glucose monitoring in adolescents with obesity: monitoring of glucose profiles, glycemic excursions, and adherence to time restricted eating programs. Front Endocrinol. 2022;13:841838.

    Article  Google Scholar 

  193. Kahleova H, et al. Eating two larger meals a day (breakfast and lunch) is more effective than six smaller meals in a reduced-energy regimen for patients with type 2 diabetes: a randomised crossover study. Diabetologia. 2014;57(8):1552–60.

    Article  Google Scholar 

  194. Carlson O, et al. Impact of reduced meal frequency without caloric restriction on glucose regulation in healthy, normal-weight middle-aged men and women. Metabolism. 2007;56:1729–34.

    Article  CAS  Google Scholar 

  195. Tinsley GM, et al. Time-restricted feeding in young men performing resistance training: a randomized controlled trial. Eur J Sport Sci. 2017;17(2):200–7.

    Article  Google Scholar 

  196. Karan M, et al. Sleep-wake timings in adolescence: chronotype development and associations with adjustment. J Youth Adolesc. 2021;50(4):628–40.

    Article  Google Scholar 

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

    Article  Google Scholar 

  198. da Silveira KSR, et al. Association among chronotype, dietary behaviours, and caries experience in Brazilian adolescents: is there a behavioural pattern? Int J Paediatr Dent. 2018;28(6):608–15.

    Article  Google Scholar 

  199. Mazri FH, et al. The association between chronotype and dietary pattern among adults: a scoping review. Int J Environ Res Public Health. 2019;17(1):68.

    Article  Google Scholar 

  200. Terschuren C, et al. Association of dietary pattern, lifestyle and chronotype with metabolic syndrome in elderly-lessons from the population-based Hamburg city health study. Int J Environ Res Public Health. 2021;19(1):377.

    Article  Google Scholar 

  201. Hagenauer MH, et al. Adolescent changes in the homeostatic and circadian regulation of sleep. Dev Neurosci. 2009;31(4):276–84.

    Article  CAS  Google Scholar 

  202. Hagenauer MH, Lee TM. Adolescent sleep patterns in humans and laboratory animals. Horm Behav. 2013;64(2):270–9.

    Article  Google Scholar 

  203. Bai S, et al. A daily diary study of sleep chronotype among Mexican-origin adolescents and parents: implications for adolescent behavioral health. Dev Psychopathol. 2021;33(1):313–22.

    Article  Google Scholar 

  204. Schlarb AA, et al. Chronotype-related differences in childhood and adolescent aggression and antisocial behavior–a review of the literature. Chronobiol Int. 2014;31(1):1–16.

    Article  Google Scholar 

  205. Paruthi S, et al. Recommended amount of sleep for pediatric populations: a consensus statement of the American Academy of Sleep Medicine. J Clin Sleep Med. 2016;12(6):785–6.

    Article  Google Scholar 

  206. Skjakodegard HF, et al. Beyond sleep duration: sleep timing as a risk factor for childhood obesity. Pediatr Obes. 2021;16(1):e12698.

    Article  Google Scholar 

  207. Duraccio KM, et al. Losing sleep by staying up late leads adolescents to consume more carbohydrates and a higher glycemic load. Sleep. 2022;45(3):zsab269.

    Article  Google Scholar 

  208. Rossbach S, et al. Relevance of chronotype for eating patterns in adolescents. Chronobiol Int. 2018;35(3):336–47.

    Article  Google Scholar 

  209. Chaput JP, Saunders TJ, Carson V. Interactions between sleep, movement and other non-movement behaviours in the pathogenesis of childhood obesity. Obes Rev. 2017;18(Suppl 1):7–14.

    Article  Google Scholar 

  210. Eckel RH, et al. Morning circadian misalignment during short sleep duration impacts insulin sensitivity. Curr Biol. 2015;25(22):3004–10.

    Article  CAS  Google Scholar 

  211. Koren D, et al. Sleep architecture and glucose and insulin homeostasis in obese adolescents. Diabetes Care. 2011;34(11):2442–7.

    Article  CAS  Google Scholar 

  212. Touitou Y. Adolescent sleep misalignment: a chronic jet lag and a matter of public health. J Physiol Paris. 2013;107(4):323–6.

    Article  Google Scholar 

  213. Withrow D, et al. Sleep and circadian disruption and the gut microbiome-possible links to dysregulated metabolism. Curr Opin Endocr Metab Res. 2021;17:26–37.

    Article  CAS  Google Scholar 

  214. Zhu Y, et al. Association between sleep architecture and glucose tolerance in children and adolescents. J Diabetes. 2015;7(1):10–5.

    Article  CAS  Google Scholar 

  215. Najem J, et al. Prevalence of food addiction and association with stress, sleep quality and chronotype: a cross-sectional survey among university students. Clin Nutr. 2020;39(2):533–9.

    Article  Google Scholar 

  216. St-Onge MP, et al. Sleep and meal timing influence food intake and its hormonal regulation in healthy adults with overweight/obesity. Eur J Clin Nutr. 2019;72(Suppl 1):76–82.

    Article  CAS  Google Scholar 

  217. Shamsuzzaman A, et al. Glucose, insulin, and insulin resistance in normal-weight, overweight and obese children with obstructive sleep apnea. Obes Res Clin Pract. 2014;8(6):e584–91.

    Article  Google Scholar 

  218. Torres-Castillo N, et al. Healthy obese subjects differ in chronotype, sleep habits, and adipose tissue fatty acid composition from their non-healthy counterparts. Nutrients. 2020;13(1):119.

    Article  Google Scholar 

  219. Wheaton AG, Chapman DP, Croft JB. School start times, sleep, behavioral, health, and academic outcomes: a review of the literature. J Sch Health. 2016;86(5):363–81.

    Article  Google Scholar 

  220. Rasberry JE, et al. Movement behaviors and health-related fitness among peripubertal adolescents: 2012 NHANES national youth fitness survey data. J Sports Med Phys Fitness. 2021;61(7):983–90.

    Article  Google Scholar 

  221. Sriram K, et al. The dose-response relationship between physical activity and cardiometabolic health in adolescents. Am J Prev Med. 2021;60(1):95–103.

    Article  Google Scholar 

  222. Banwell C, et al. Reflections on expert consensus: a case study of the social trends contributing to obesity. Eur J Public Health. 2005;15(6):564–8.

    Article  Google Scholar 

  223. Brown H, Roberts J. Exercising choice: the economic determinants of physical activity behaviour of an employed population. Soc Sci Med. 2011;73(3):383–90.

    Article  Google Scholar 

  224. Chinn DJ, et al. Barriers to physical activity and socioeconomic position: implications for health promotion. J Epidemiol Community Health. 1999;53(3):191–2.

    Article  CAS  Google Scholar 

  225. Jabs J, Devine CM. Time scarcity and food choices: an overview. Appetite. 2006;47(2):196–204.

    Article  Google Scholar 

  226. Sherwood NE, Jeffery RW. The behavioral determinants of exercise: implications for physical activity interventions. Annu Rev Nutr. 2000;20:21.

    Article  CAS  Google Scholar 

  227. Escoto KH, et al. Work hours and perceived time barriers to healthful eating among young adults. Am J Health Behav. 2012;36(6):786–96.

    Article  Google Scholar 

  228. Braveman P, Gottlieb L. The social determinants of health: it’s time to consider the causes of the causes. Public Health Rep. 2014;129(Suppl 2):19–31.

    Article  Google Scholar 

  229. Roberts JD, et al. Between privilege and oppression: an intersectional analysis of active transportation experiences among Washington D.C. Area Youth. Int J Environ Res Public Health. 2019;16(8):1313.

    Article  Google Scholar 

  230. Cairney J, et al. Children’s participation in organized sport and physical activities and active free play: exploring the impact of time, gender and neighbourhood household income using longitudinal data. Sociol Sport J. 2015;32(3):266–83.

    Article  Google Scholar 

  231. Okely T, et al. Cross-sectional examination of 24 hour movement behaviours among 3- and 4-year-old children in urban and rural settings in low-income, middle-income and high-income countries: the SUNRISE study protocol. BMJ Open. 2021;11(10):e049267.

    Article  Google Scholar 

  232. Lee E-Y, et al. Levels and correlates of 24 hour movement behaviors among South Koreans: results from the Korea National Health and Nutrition Examination Surveys, 2014 and 2015. J Sport Health Sci. 2019;8(4):376–85.

    Article  Google Scholar 

  233. Chen E, Matthews KA, Boyce WT. Socioeconomic differences in children’s health: how and why do these relationships change with age? Psychol Bull. 2002;128(2):295–329.

    Article  Google Scholar 

  234. Humbert ML, et al. Factors that influence physical activity participation among high- and low-SES youth. Qual Health Res. 2006;16(4):467–83.

    Article  Google Scholar 

  235. Eime RM, et al. The relationship of sport participation to provision of sports facilities and socioeconomic status: a geographical analysis. Aust N Z J Public Health. 2017;41(3):248–55.

    Article  Google Scholar 

  236. Fairclough SJ, et al. Associations between children’s socioeconomic status, weight status, and sex, with screen-based sedentary behaviours and sport participation. Int J Pediatr Obes. 2009;4(4):299–305.

    Article  Google Scholar 

  237. Kanters MA, et al. School sport participation under two school sport policies: comparisons by race/ethnicity, gender, and socioeconomic status. Ann Behav Med. 2013;45(Suppl 1):S113–21.

    Article  Google Scholar 

  238. Vandendriessche JB, et al. Variation in sport participation, fitness and motor coordination with socioeconomic status among Flemish children. Pediatr Exerc Sci. 2012;24(1):113–28.

    Article  Google Scholar 

  239. Ferraro KF, Farmer MM. Double jeopardy to health hypothesis for African Americans: analysis and critique. J Health Soc Behav. 1996;37(1):27–43.

    Article  CAS  Google Scholar 

  240. Taylor D, Richards D. Triple Jeopardy: complexities of racism, sexism, and ageism on the experiences of mental health stigma among young Canadian Black women of Caribbean descent. Front Sociol. 2019;4:43.

    Article  Google Scholar 

  241. Tremblay MS, et al. Canadian sedentary behaviour guidelines for the early years (aged 0–4 years). Appl Physiol Nutr Metab. 2012;37(2):370–91.

    Article  Google Scholar 

  242. Tremblay MS, et al. Canadian physical activity guidelines for the early years (aged 0–4 years). Appl Physiol Nutr Metab. 2012;37(2):345–69.

    Article  Google Scholar 

  243. American College of Sports Medicine. ACSM's guidelines for exercise testing and prescription. 11th ed. Philadelphia; 2021.

  244. Owens J, Adolescent Sleep Working Group, Committee on Adolescence. Insufficient sleep in adolescents and young adults: an update on causes and consequences. Pediatrics. 2014;134(3):e921–32.

    Article  Google Scholar 

  245. Paruthi S, et al. Consensus statement of the American Academy of Sleep Medicine on the recommended amount of sleep for healthy children: methodology and discussion. J Clin Sleep Med. 2016;12(11):1549–61.

    Article  Google Scholar 

Download references

Acknowledgements

The manuscript was partially supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK; 1R01DK130851, Salvy), the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD; R01HD092483; de la Haye/Salvy), the National Cancer Institute (NCI; R01CA258222; Figueiredo/Salvy/ Peterson), and the Hope Warschaw Center for Integrated Research in Cancer and Lifestyle Award (Salvy). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIDDK, the NICHD, the NCI, or the Hope Warschaw foundation.

Funding

The manuscript was partially supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK; 1R01DK130851, Salvy), the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD; R01HD092483; de la Haye/Salvy), the National Cancer Institute (NCI; R01CA258222; Figueiredo/Salvy/ Peterson) and the Hope Warschaw Center for Integrated Research in Cancer and Lifestyle Award (Salvy). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIDDK, the NICHD, the NCI, or the Hope Warschaw foundation.

Author information

Authors and Affiliations

  1. Department of Pediatrics, Center for Endocrinology, Diabetes and Metabolism, Children’s Hospital Los Angeles and Keck School of Medicine of USC, 4650 Sunset Boulevard, Mailstop #61, Los Angeles, CA, 90027, USA

    Alaina P. Vidmar

  2. Cancer Research Center On Health Equity, Cedars-Sinai Medical Center, West Hollywood, CA, USA

    Nenette A. Cáceres, Celina Shirazipour & Sarah-Jeanne Salvy

  3. Department of Nutrition Sciences, University of Alabama at Birmingham, Birmingham, AL, USA

    Camille R. Schneider-Worthington

  4. College of Health Solutions, Arizona State University, Tempe, USA

    Matthew P. Buman

  5. Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA

    Kayla de la Haye & Sarah-Jeanne Salvy

Authors
  1. Alaina P. Vidmar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nenette A. Cáceres
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Camille R. Schneider-Worthington
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Celina Shirazipour
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Matthew P. Buman
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Kayla de la Haye
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Sarah-Jeanne Salvy
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

APV, NAC, CRSW, CS, MPB, KH, and SJS conceptualized and designed the study, drafted the initial manuscript, and reviewed and revised the manuscript. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

Corresponding author

Correspondence to Alaina P. Vidmar.

Ethics declarations

Conflict of Interest

The additional authors have no financial relationships or conflict of interest to disclose.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is part of the Topical Collection on Childhood Obesity

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Vidmar, A.P., Cáceres, N.A., Schneider-Worthington, C.R. et al. Integration of Time-Based Recommendations with Current Pediatric Health Behavior Guidelines: Implications for Obesity Prevention and Treatment in Youth. Curr Obes Rep 11, 236–253 (2022). https://doi.org/10.1007/s13679-022-00491-z

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13679-022-00491-z

Keywords

Search

Navigation