The effect of replacing sedentary behavior by different intensities of physical activity in body composition: a systematic review

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Melyssa Alves Souza
Thatiane Lopes Valentim Di Paschoale Ostolin


Introduction: The isotemporal substitution model (ISM) is a statistical approach that estimates the effects of replacing, in minutes, a block of physical activity or sedentary behavior by another block with different intensity. Previous studies have used the ISM to evaluate the effect of different isotemporal substitutions on body composition. Thus, the ISM can contribute to the understanding of changes in body composition related to distinct lifestyles and, hence, guiding future recommendations for maintaining and/or improving body composition. Objective: To review the effect of replacing sedentary behavior by physical activity on body composition change analyzed through ISM. Methods: Original articles in English were identified from searches in PubMed and Periódicos Capes databases. The search was carried out by two researchers. Last search was performed in October 2020. Results: A total of 17 included articles, which evaluated different applications of ISM in relation to body composition change, mostly obtained by BMI and body fat. The physical activity was mainly assessed by using an accelerometer. Several methodological differences among the included studies limited comparisons between findings, including the sample profile and cut off points for physical activity. Conclusion: Among the studies that evaluate the effect of replacing sedentary behavior for different intensities of physical activity through ISM, replacing sedentary behavior by moderate-to-vigorous physical activity presented a more consistent effect in body composition change in comparison to replacement by other physical activity intensities, even for small blocks of time (five minutes).


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How to Cite
Souza, M. A., & Ostolin, T. L. V. D. P. (2021). The effect of replacing sedentary behavior by different intensities of physical activity in body composition: a systematic review. ABCS Health Sciences, 46, e021304.
Review Articles
Author Biography

Melyssa Alves Souza, Laboratório de Diabetes Experimental e Sinalização Celular, Universidade Federal de São Paulo (UNIFESP) – Santos (SP), Brazil

Biociences Department


1. Mekary RA, Willett WC, Hu FB, Ding EL. Isotemporal substitution paradigm for physical activity epidemiology and weight change. Am J Epidemiol. 2009;170(4):519-27.

2. Willett W, Stampfer MJ. Total energy intake: Implications for epidemiologic analyses. Am J Epidemiol. 1986;124(1):17-27.

3. Willett WC, Howe GR, Kushi LH. Adjustment for total energy intake in epidemiologic studies. Am J Clin Nutr. 1997;65(4 Suppl):1220S-8S.

4. Dumuid D, Wake M, Clifford S, Burgner D, Carlin JB, Mensah FK, et al. The Association of the Body Composition of Children with 24-Hour Activity Composition. J Pediatr. 2019;208:43-9.e9.

5. Pedišić Ž, Dumuid D, Olds TS. Integrating sleep, sedentary behaviour, and physical activity research in the emerging fied of time-use epidemiology: Definitions, concepts, statistical methods, theoretical framework, and future directions. Kinesiology. 2017;49(2):1-17.

6. American College of Sports Medicine (ACSM). Guidelines for exercise testing and prescription. 10th edition. Philadelphia: Wolters Kluwer Health, 2018.

7. Keane E, Li X, Harrington JM, Fitzgerald AP, Perry IJ, Kearney PM. Physical activity, sedentary behavior and the risk of overweight and obesity in school-aged children. Pediatr Exerc Sci. 2017;29(3):408-18.

8. McPhee JS, French DP, Jackson D, Nazroo J, Pendleton N, Degens H. Physical activity in older age: perspectives for healthy ageing and frailty. Biogerontology. 2016;17(3):567-80.

9. World Health Organization (WHO). Physical activity. Available from:

10. Wu XY, Han LH, Zhang JH, Luo S, Hu JW, Sun K. The influence of physical activity, sedentary behavior on health-related quality of life among the general population of children and adolescents: A systematic review. PLoS One. 2017;12(11):e0187668.

11. Rezende LFM, Rey-López JP, Matsudo VKR, Luiz ODC. Sedentary behavior and health outcomes among older adults: A systematic review. BMC Public Health. 2014;14:333.

12. Mekary RA, Ding EL. Isotemporal Substitution as the Gold Standard Model for Physical Activity Epidemiology: Why It Is the Most Appropriate for Activity Time Research. Int J Environ Res Public Health. 2019;16(5):797.

13. World Health Organization (WHO). Physical status: the use and interpretation of Anthropometry. Available from:

14. Leppänen MH, Henriksson P, Delisle Nyström C, Henriksson H, Ortega FB, Pomeroy J, et al. Longitudinal physical activity, body composition, and physical fitness in preschoolers. Med Sci Sports Exerc. 2017;49(10):2078-85.

15. Matsudo S, Araujo T, Matsudo V, Andrade D, Andrade E, Oliveira LC, et al. Questionario Internacional de Atividade Física (IPAQ): estudo de validade e reprodutibilidade no Brasil. Soc Bras Ativ Fis Saude. 2001;6(2):5-18.

16. Migueles JH, Cadenas-Sanchez C, Ekelund U, Nyström CD, Mora-Gonzalez J, Löf M, et al. Accelerometer data collection and processing criteria to assess physical activity and other outcomes: a systematic review and practical considerations. Sport Med. 2017;47(9):1821-45.

17. Skender S, Ose J, Chang-Claude J, Paskow M, Brühmann B, Siegel EM, Steindorf K, et al. Accelerometry and physical activity questionnaires - a systematic review. BMC Public Health. 2016;16:515.

18. Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group. Principais itens para relatar Revisões sistemáticas e Meta-análises: a recomendação PRISMA. Epidemiol Serv Saude. 2015;24(2):335-42.

19. Falconer CL, Page AS, Andrews RC, Cooper AR. The potential impact of displacing sedentary time in adults with type 2 Diabetes. Med Sci Sports Exerc. 2015;47(10):2070-5.

20. Ferreira RW, Rombaldi AJ, Ricardo LIC, Hallal PC, Azevedo MR. Prevalence of sedentary behavior and its correlates among primary and secondary school students. Rev Paul Pediatr. 2016;34(1):56-63.

21. Varela-Mato V, O’Shea O, King JA, Yates T, Stensel DJ, Biddle SJ, et al. Cross-sectional surveillance study to phenotype lorry drivers’ sedentary behaviours, physical activity and cardio-metabolic health. BMJ Open. 2017;7(6):e013162.

22. Danquah IH, Pedersen ESL, Petersen CB, Aadahl M, Holtermann A, Tolstrup JS. Estimated impact of replacing sitting with standing at work on indicators of body composition: Cross-sectional and longitudinal findings using isotemporal substitution analysis on data from the Take a Stand! study. PLoS One. 2018;13(6):e0198000.

23. Collings PJ, Brage S, Bingham DD, Costa S, West J, Mceachan RRC, et al. Physical Activity, Sedentary Time, and Fatness in a Biethnic Sample of Young Children. Med Sci Sports Exerc. 2017;49(5):930-8.

24. Leppanen MH, Nystrom CD, Henriksson P, Pomeroy J, Ruiz JR, Ortega FB, et al. Physical activity intensity, sedentary behavior, body composition and physical fitness in 4-year-old children: results from the ministop trial. Int J Obes. 2016;40(7):1126-33.

25. Aggio D, Smith L, Hamer M. Effects of reallocating time in different activity intensities on health and fitness: A cross sectional study. Int J Behav Nutr Phys Act. 2015;12:83.

26. Del Pozo-Cruz B, Gant N, Del Pozo-Cruz J, Maddison R. Relationships between sleep duration, physical activity and body mass index in young New Zealanders: An isotemporal substitution analysis. PLoS One. 2017;12(9):e0184472.

27. Collings PJ, Westgate K, Väistö J, Wijndaele K, Atkin AJ, Haapala EA, et al. Cross-Sectional Associations of Objectively-Measured Physical Activity and Sedentary Time with Body Composition and Cardiorespiratory Fitness in Mid-Childhood: The PANIC Study. Sport Med. 2017;47(4):769-80.

28. Loprinzi PD, Cardinal BJ, Lee H, Tudor-Locke C. Markers of adiposity among children and adolescents: implications of the isotemporal substitution paradigm with sedentary behavior and physical activity patterns. J Diabetes Metab Disord. 2015;14:46.

29. Jones MA, Skidmore PM, Stoner L, Harrex H, Saeedi P, Black K, et al. Associations of accelerometer-measured sedentary time, sedentary bouts, and physical activity with adiposity and fitness in children. J Sports Sci. 2020;38(1):114-20.

30. Tan K, Cai L, Lai L, Gui Z, Zeng X, Lv Y, et al. Association of reallocating time in different intensities of physical activity with weight status changes among normal-weight chinese children: A national prospective study. Int J Environ Res Public Health. 2020;17(16):5761.

31. Dumuid D, Stanford TE, Pedi Z, Maher C, Lewis LK, Martín-Fernandez JA, et al. Adiposity and the isotemporal substitution of physical activity, sedentary time and sleep among school-aged children: a compositional data analysis approach. BMC Public Health. 2018;18;311.

32. Oviedo-Caro MA, Bueno-Antequera J, Munguía-Izquierdo D. Associations of 24-hours activity composition with adiposity and cardiorespiratory fitness: the PregnActive project. Scand J Med Sci Sport. 2020;30(2):295-302.

33. Dahl-Petersen IK, Brage S, Bjerregaard P, Tolstrup J, Jorgensen ME. Physical activity and abdominal fat distribution in Greenland. Med Sci Sports Exerc. 2017;49(10):2064-70.

34. Galmes-Panades AM, Varela-Mato V, Konieczna J, Wärnberg J, Martínez-González MA, Salas-Salvadó J, et al. Isotemporal substitution of inactive time with physical activity and time in bed: Cross-sectional associations with cardiometabolic health in the PREDIMED-Plus study. Int J Behav Nutr Phys Act. 2019;16:137.

35. Boyle T, Vallance JK, Buman MP, Lynch BM. Reallocating time to sleep, sedentary time, or physical activity: Associations with waist circumference and body mass index in breast cancer survivors. Cancer Epidemiol Biomarkers Prev. 2017;26(2):254-60.

36. Curtis RG, Dumuid D, Olds T, Plotnikoff R, Vandelanotte C, Ryan J, et al. The association between time-use behaviors and physical and mental well-being in adults: a compositional isotemporal substitution analysis. J Phys Act Heal. 2020;17(2):197-203.

37. Freedson PS, Melanson E, Sirard J. Calibration of the Computer Science and Applications, Inc. accelerometer. Med Sci Sports Exerc. 1998;30(5):777-81.

38. Freedson P, Pober D, Janz KF. Calibration of accelerometer output for children. Med Sci Sports Exerc. 2005;37(11 Suppl):S523-30.

39. Evenson KR, Catellier DJ, Gill K, Ondrak KS, McMurray RG. Calibration of two objective measures of physical activity for children. J Sports Sci. 2008;26(1):1557-65.

40. Booth FW, Roberts CK, Thyfault JP, Ruegsegger GN, Toedebusch RG. Role of inactivity in chronic diseases: Evolutionary insight and pathophysiological mechanisms. Physiol Rev. 2017;97(4):1351-1402.

41. Trost SG, Loprinzi PD, Moore R, Pfeiffer KA. Comparison of accelerometer cut points for predicting activity intensity in youth. Med Sci Sports Exerc. 2011;43(7):1360-8.

42. Strath SJ, Bassett DR, Swartz AM. Comparison of MTI accelerometer cut-points for predicting time spent in physical activity. Int J Sports Med. 2003;24(4):298-303.

43. Bianchim MS, McNarry MA, Larun L, Mackintosh KA, ActiveYouth SRC group, Applied Sports Science Technology, et al. Calibration and validation of accelerometry to measure physical activity in adult clinical groups: a systematic review. Prev Med Rep. 2019;16:101001.

44. Colley RC, Tremblay MS. Moderate and vigorous physical activity intensity cut-points for the Actical accelerometer. J Sports Sci. 2011;29(8):783-9.

45. World Health Organization (WHO). Obesity and overweight. Available from:

46. Nittari G, Scuri S, Petrelli F, Pirillo I, Di Luca NM, Grappasonni I. Fighting obesity in children from European World Health Organization member states. Epidemiological data, medical-social aspects, and prevention programs. Clin Ter. 2019;170(3):e223-30.

47. Spinelli A, Buoncristiano M, Kovacs VA, Yngve A, Spiroski I, Obreja G, et al. Prevalence of severe obesity among primary school children in 21 European countries. Obes Facts. 2019;12(2):244-58.

48. Rivera JA, Cossío TG, Pedraza LS, Aburto TC, Sánchez TG, Martorell R. Childhood and adolescent overweight and obesity in Latin America: A systematic review. Lancet Diabetes Endocrinol. 2014;2(4):321-32.

49. Marques A, Peralta M, Naia A, Loureiro N, Matos MG. Prevalence of adult overweight and obesity in 20 European countries, 2014. Eur J Public Health. 2018;28(2):295-300.

50. Hales CM, Fryar CD, Carroll MD, Freedman DS, Ogden CL. Trends in obesity and severe obesity prevalence in US youth and adults by sex and age, 2007-2008 to 2015-2016. JAMA. 2018;319(16):1723-5.

51. Kalish VB. Obesity in older adults. Prim Care Clin Office Pract. 2016;43:137-44.

52. Brasil. Ministério da Saúde. Secretaria de Atenção à Saúde. Departamento de Atenção Básica. Guia Alimentar para a População Brasileira. 2 ed. Brasília: Ministério da Saúde. 2014.

53. American Institutes for Reserch (AIR). Federal Interagency Forum on Aging-Related Statistics. Available from:

54. Zink J, Belcher BR, Imm K, Leventhal AM. The relationship between screen-based sedentary behaviors and symptoms of depression and anxiety in youth: a systematic review of moderating variables. BMC Public Health. 2020;20:472.

55. Shaphe MA, Chahal A. Relation of physical activity with the depression: a short review. J Lifestyle Med. 2020;10(1):1-6.

56. Grgic J, Dumuid D, Bengoechea EG, Shrestha N, Bauman A, Olds T, et al. Health outcomes associated with reallocations of time between sleep, sedentary behaviour, and physical activity: A systematic scoping review of isotemporal substitution studies. Int J Behav Nutr Phys Act. 2018;15(1):69.