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Health Benefits of Light-Intensity Physical Activity: A Systematic Review of Accelerometer Data of the National Health and Nutrition Examination Survey (NHANES)

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Abstract

Background

The health effects of light-intensity physical activity (PA) are not well known today.

Objective

We conducted a systematic review to assess the association of accelerometer-measured light-intensity PA with modifiable health outcomes in adults and older adults.

Methods

A systematic literature search up to March 2016 was performed in the PubMed, EMBASE, Web of Science and Google Scholar electronic databases, without language limitations, for studies of modifiable health outcomes in adults and older adults in the National Health and Nutrition Examination Survey accelerometer dataset.

Results

Overall, 37 cross-sectional studies and three longitudinal studies were included in the analysis, with considerable variation observed between the studies with regard to their operationalization of light-intensity PA. Light-intensity PA was found to be beneficially associated with obesity, markers of lipid and glucose metabolism, and mortality. Few data were available on musculoskeletal outcomes and results were mixed.

Conclusions

Observational evidence that light-intensity PA can confer health benefits is accumulating. Currently inactive or insufficiently active people should be encouraged to engage in PA of any intensity. If longitudinal and intervention studies corroborate our findings, the revision of PA recommendations to include light-intensity activities, at least for currently inactive populations, might be warranted.

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References

  1. Booth FW, Roberts CK, Laye MJ. Lack of exercise is a major cause of chronic diseases. Compr Physiol. 2012;2(2):1143–211.

    PubMed  PubMed Central  Google Scholar 

  2. Lee I, Shiroma EJ. Using accelerometers to measure physical activity in large-scale epidemiological studies: issues and challenges. Br J Sports Med. 2014;48(3):197–201.

    Article  PubMed  Google Scholar 

  3. Shephard RJ. Limits to the measurement of habitual physical activity by questionnaires. Br J Sports Med. 2003;37(3):197–206.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Finger JD, Tafforeau J, Gisle L, et al. Development of the European Health Interview Survey-Physical Activity Questionnaire (EHIS-PAQ) to monitor physical activity in the European Union. Arch Public Health. 2015;2(73):59.

    Article  Google Scholar 

  5. World Health Organization. Global recommendations on physical activity for health. Geneva: World Health Organization; 2010. Available at: http://apps.who.int/iris/bitstream/10665/44399/1/9789241599979_eng.pdf.

  6. Healy GN, Wijndaele K, Dunstan DW, et al. Objectively measured sedentary time, physical activity, and metabolic risk: the Australian Diabetes, Obesity and Lifestyle Study (AusDiab). Diabetes Care. 2008;31(2):369–71.

    Article  PubMed  Google Scholar 

  7. Centers for Disease Control and Prevention. National Health and Nutrition Examination Survey. Available from: http://www.cdc.gov/nchs/nhanes.htm.

  8. Centers for Disease Control and Prevention. Key concepts about physical activity monitor data collection methods. Available at: http://www.cdc.gov/nchs/tutorials/PhysicalActivity/SurveyOrientation/DataOverview/Info2c.htm.

  9. McClain JJ, Sisson SB, Tudor-Locke C. Actigraph accelerometer interinstrument reliability during free-living in adults. Med Sci Sports Exerc. 2007;39(9):1509–14.

    Article  PubMed  Google Scholar 

  10. Moher D, Liberati A, Tetzlaff J, et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Liberati A, Altman DG, Tetzlaff J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ. 2009;339:b2700.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Tudor-Locke C, Camhi SM, Troiano RP. A catalog of rules, variables, and definitions applied to accelerometer data in the National Health and Nutrition Examination Survey, 2003–2006. Prev Chronic Dis. 2012;9:E113.

    PubMed  PubMed Central  Google Scholar 

  13. Stroup DF, Berlin JA, Morton SC, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA. 2000;283:2008–12.

    Article  CAS  PubMed  Google Scholar 

  14. Sanderson S, Tatt ID, Higgins JP. Tools for assessing quality and susceptibility to bias in observational studies in epidemiology: a systematic review and annotated bibliography. Int J Epidemiol. 2007;36(3):666–76.

    Article  PubMed  Google Scholar 

  15. Shamliyan T, Kane RL, Dickinson S. A systematic review of tools used to assess the quality of observational studies that examine incidence or prevalence and risk factors for diseases. J Clin Epidemiol. 2010;63(10):1061–70.

    Article  PubMed  Google Scholar 

  16. von Elm E, Altman DG, Egger M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Prev Med. 2007;45:247–51.

    Article  Google Scholar 

  17. Ariëns GA, van Mechelen W, Bongers PM, et al. Physical risk factors for neck pain. Scand J Work Environ Health. 2000;26:7–19.

    Article  PubMed  Google Scholar 

  18. Cliff DP, Hesketh KD, Vella SA, et al. Objectively measured sedentary behaviour and health and development in children and adolescents: systematic review and meta-analysis. Obes Rev. 2016;17:330–44.

    Article  CAS  PubMed  Google Scholar 

  19. Buman MP, Winkler EA, Kurka JM, et al. Reallocating time to sleep, sedentary behaviors, or active behaviors: associations with cardiovascular disease risk biomarkers, NHANES 2005–2006. Am J Epidemiol. 2014;179(3):323–34.

    Article  PubMed  Google Scholar 

  20. Camhi SM, Sisson SB, Johnson WD, et al. Accelerometer-determined moderate intensity lifestyle activity and cardiometabolic health. Prev Med. 2011;52:358–60.

    Article  PubMed  Google Scholar 

  21. Chastin SFM, Mandrichenko O, Helbostadt JL, et al. Associations between objectively-measured sedentary behaviour and physical activity with bone mineral density in adults and older adults, the NHANES study. Bone. 2014;64:254–62.

    Article  CAS  PubMed  Google Scholar 

  22. Chastin SFM, Palarea-Albaladejo J, Dontje ML, 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:e0139984.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Dansie EJ, Turk DC, Martin KR, et al. Association of chronic widespread pain with objectively measured physical activity in adults: findings from the National Health and Nutrition Examination survey. J Pain. 2014;15(5):507–15.

    Article  PubMed  Google Scholar 

  24. Gay JL, Buchner DM, Schmidt MD. Dose–response association of physical activity with HbA1c: intensity and bout length. Prev Med. 2016;86:58–63.

    Article  PubMed  Google Scholar 

  25. Gerber L, Otgonsuren M, Mishra A, et al. Non-alcoholic fatty liver disease (NAFLD) is associated with low level of physical activity: a population-based study. Aliment Pharmacol Ther. 2012;36:772–81.

    Article  CAS  PubMed  Google Scholar 

  26. Hawkins M, Belalcazar LM, Schelbert KB, et al. The effect of various intensities of physical activity and chronic inflammation in men and women by diabetes status in a national sample. Diabetes Res Clin Pract. 2012;97:e6–8.

    Article  PubMed  Google Scholar 

  27. Hawkins M, Pekow P, Chasan-Taber L. Physical activity, sedentary behavior, and C-reactive protein in pregnancy. Med Sci Sports Exerc. 2014;46:284–92.

    Article  CAS  PubMed  Google Scholar 

  28. Hawkins MS, Gabriel KP, Conroy MB, et al. Physical activity intensity and cardiovascular risk by ankle-brachial index. Vasc Med. 2013;18:79–84.

    Article  PubMed  Google Scholar 

  29. Hawkins MS, Sevick MA, Richardson CR, et al. Association between physical activity and kidney function: National Health and Nutrition Examination Survey. Med Sci Sports Exerc. 2011;43:1457–64.

    Article  PubMed  Google Scholar 

  30. Howard B, Winkler EA, Sethi P, et al. Associations of low- and high-intensity light activity with cardiometabolic biomarkers. Med Sci Sports Exerc. 2015;47:2093–101.

    Article  CAS  PubMed  Google Scholar 

  31. Liu S, Waring ME, Eaton CB, et al. Association of objectively measured physical activity and metabolic syndrome among US adults with osteoarthritis. Arthritis Care Res. 2015;67:1371–8.

    Article  Google Scholar 

  32. Loprinzi PD. Objectively measured light and moderate-to-vigorous physical activity is associated with lower depression levels among older US adults. Aging Ment Health. 2013;17:801–5.

    Article  PubMed  Google Scholar 

  33. Loprinzi PD. Accelerometer-determined sedentary and physical activity estimates among older adults with diabetes: considerations by demographic and comorbidity characteristics. J Aging Phys Act. 2014;22:432–40.

    Article  PubMed  Google Scholar 

  34. Loprinzi PD. Effects of light-intensity physical activity on red blood cell distribution width: implications for a novel mechanism through which light-intensity physical activity may influence cardiovascular disease. Int J Cardiol. 2016;203:724–5.

    Article  PubMed  Google Scholar 

  35. Loprinzi PD, Brosky JA Jr. Objectively measured physical activity and balance among U.S. adults. J Strength Cond Res. 2014;28:2290–6.

    Article  PubMed  Google Scholar 

  36. Loprinzi PD, Kohli M. Effect of physical activity and sedentary behavior on serum prostate-specific antigen concentrations: results from the National Health and Nutrition Examination Survey (NHANES), 2003–2006. Mayo Clin Proc. 2013;88:11–21.

    Article  CAS  PubMed  Google Scholar 

  37. Loprinzi PD, Lee H. Rationale for promoting physical activity among cancer survivors: literature review and epidemiologic examination. Oncol Nurs Forum. 2014;41:117–25.

    Article  PubMed  Google Scholar 

  38. Loprinzi PD, Lee H, Cardinal BJ. Dose response association between physical activity and biological, demographic, and perceptions of health variables. Obes Facts. 2013;6:380–92.

    Article  PubMed  Google Scholar 

  39. Loprinzi PD, Lee H, Cardinal BJ. Objectively measured physical activity among US cancer survivors: considerations by weight status. J Cancer Surviv. 2013;7:493–9.

    Article  PubMed  Google Scholar 

  40. Loprinzi PD, Lee H, Cardinal BJ. Evidence to support including lifestyle light-intensity recommendations in physical activity guidelines for older adults. Am J Health Promot. 2015;29:277–84.

    Article  PubMed  Google Scholar 

  41. Loprinzi PD, Lee H, Gilham B, et al. Association between accelerometer-assessed physical activity and tinnitus, NHANES 2005–2006. Res Q Exerc Sport. 2013;84:177–85.

    Article  PubMed  Google Scholar 

  42. Loprinzi PD, Pariser G. Physical activity intensity and biological markers among adults with diabetes: considerations by age and gender. J Diabetes Complicat. 2013;27:134–40.

    Article  PubMed  Google Scholar 

  43. Loprinzi PD, Pariser G, Ramulu PY. Accelerometer-assessed sedentary and physical activity behavior and its association with vision among U.S. adults with diabetes. J Phys Act Health. 2014;11:1156–61.

    Article  PubMed  Google Scholar 

  44. Loprinzi PD, Ramulu PY. Objectively measured physical activity and inflammatory markers among US adults with diabetes: implications for attenuating disease progression. Mayo Clin Proc. 2013;88:942–51.

    Article  PubMed  Google Scholar 

  45. Loprinzi PD, Sheffield J, Tyo BM, et al. Accelerometer-determined physical activity, mobility disability, and health. Disabil Health J. 2014;7:419–25.

    Article  PubMed  Google Scholar 

  46. Loprinzi PD, Walker JF, Lee H. Association between physical activity and inflammatory markers among U.S. adults with chronic obstructive pulmonary disease. Am J Health Promot. 2014;29:81–8.

    Article  PubMed  Google Scholar 

  47. Lynch BM, Dunstan DW, Winkler E, et al. Objectively assessed physical activity, sedentary time and waist circumference among prostate cancer survivors: findings from the National Health and Nutrition Examination Survey (2003–2006). Eur J Cancer Care. 2011;20:514–9.

    Article  CAS  Google Scholar 

  48. Lynch BM, Dunstan DW, Healy GN, et al. Objectively measured physical activity and sedentary time of breast cancer survivors, and associations with adiposity: findings from NHANES (2003–2006). Cancer Causes Control. 2010;21:283–8.

    Article  PubMed  Google Scholar 

  49. Lynch BM, Friedenreich CM, Winkler EA, et al. Associations of objectively assessed physical activity and sedentary time with biomarkers of breast cancer risk in postmenopausal women: findings from NHANES (2003–2006). Breast Cancer Res Treat. 2011;130:183–94.

    Article  PubMed  Google Scholar 

  50. Park SK, Larson JL. The relationship between physical activity and metabolic syndrome in people with chronic obstructive pulmonary disease. J Cardiovasc Nurs. 2014;29:499–507.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Park SK, Richardson CR, Holleman RG, et al. Physical activity in people with COPD, using the National Health and Nutrition Evaluation Survey dataset (2003–2006). Heart Lung. 2013;42:235–40.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Prizer LP, Gay JL, Gerst-Emerson K, et al. The role of age in moderating the association between disability and light-intensity physical activity. Am J Health Promot. 2016;30:e101–9.

    Article  PubMed  Google Scholar 

  53. Robson J, Janssen I. Intensity of bouted and sporadic physical activity and the metabolic syndrome in adults. Peer J. 2015;3:e1437.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Smuck M, Kao MJ, Brar N, et al. Does physical activity influence the relationship between low back pain and obesity? Spine J. 2014;14:209–16.

    Article  PubMed  Google Scholar 

  55. Song MR, Lee Y, Baek J, et al. Physical activity status in adults with depression in the National Health and Nutrition Examination Survey, 2005–2006. Public Health Nurs. 2012;29:208–17.

    Article  PubMed  Google Scholar 

  56. Beddhu S, Wei G, Marcus RL, et al. Light-intensity physical activities and mortality in the United States general population and CKD subpopulation. Clin J Am Soc Nephrol. 2015;10:1145–53.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Fishman EI, Steeves JA, Zipunnikov V, et al. Association between objectively measured physical activity and mortality in NHANES. Med Sci Sports Exerc. 2016;48(7):1303–11.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Loprinzi PD. Light-intensity physical activity and all-cause mortality. Am J Health Promot. Epub 5 Jan 2016. doi:10.4278/ajhp.150515-ARB-882.

  59. Perri MG, Anton SD, Durning PE, et al. Adherence to exercise prescriptions: effects of prescribing moderate versus higher levels of intensity and frequency. Health Psychol. 2002;21:452–8.

    Article  PubMed  Google Scholar 

  60. Gando Y, Murakami H, Kawakami R, et al. Light-intensity physical activity is associated with insulin resistance in elderly Japanese women independent of moderate-to vigorous-intensity physical activity. J Phys Act Health. 2014;11:266–71.

    Article  PubMed  Google Scholar 

  61. Green AN, McGrath R, Martinez V, et al. Associations of objectively measured sedentary behavior, light activity, and markers of cardiometabolic health in young women. Eur J Appl Physiol. 2014;114:907–19.

    Article  PubMed  Google Scholar 

  62. Li J, Zhang W, Guo Q, et al. Duration of exercise as a key determinant of improvement in insulin sensitivity in type 2 diabetes patients. Tohoku J Exp Med. 2012;227:289–96.

    Article  CAS  PubMed  Google Scholar 

  63. Houmard JA, Tanner CJ, Slentz CA, et al. Effect of the volume and intensity of exercise training on insulin sensitivity. J Appl Physiol. 2004;96:101–6.

    Article  CAS  PubMed  Google Scholar 

  64. Henson J, Davies MJ, Bodicoat DH, et al. Breaking up prolonged sitting with standing or walking attenuates the postprandial metabolic response in postmenopausal women: a randomized acute study. Diabetes Care. 2016;39:130–8.

    Article  PubMed  Google Scholar 

  65. Lin X, Zhang X, Guo J, et al. Effects of exercise training on cardiorespiratory fitness and biomarkers of cardiometabolic health: a systematic review and meta-analysis of randomized controlled trials. J Am Heart Assoc. 2015;4(7). pii:e002014.

  66. Kim I, Park S, Trombold JR, et al. Effects of moderate- and intermittent low-intensity exercise on postprandial lipemia. Med Sci Sports Exerc. 2014;46:1882–90.

    Article  CAS  PubMed  Google Scholar 

  67. Duncan JJ, Gordon NF, Scott CB. Women walking for health and fitness. How much is enough? JAMA. 1991;266:3295–9.

    Article  CAS  PubMed  Google Scholar 

  68. Foong YC, Aitken D, Winzenberg T, et al. The association between physical activity and reduced body fat lessens with age—results from a cross-sectional study in community-dwelling older adults. Exp Gerontol. 2014;55:107–12.

    Article  PubMed  Google Scholar 

  69. Bann D, Hire D, Manini T, et al. Light intensity physical activity and sedentary behavior in relation to body mass index and grip strength in older adults: cross-sectional findings from the Lifestyle Interventions and Independence for Elders (LIFE) study. PLoS One. 2015;10:e0116058.

    Article  PubMed  PubMed Central  Google Scholar 

  70. Philipsen A, Hansen AS, Jørgensen ME, et al. Associations of objectively measured physical activity and abdominal fat distribution. Med Sci Sports Exerc. 2015;47:983–9.

    Article  PubMed  Google Scholar 

  71. Dowd KP, Harrington DM, Hannigan A, et al. Light-intensity physical activity is associated with adiposity in adolescent females. Med Sci Sports Exerc. 2014;46:2295–300.

    Article  PubMed  Google Scholar 

  72. Davenport MH, Giroux I, Sopper MM, et al. Postpartum exercise regardless of intensity improves chronic disease risk factors. Med Sci Sports Exerc. 2011;43:951–8.

    Article  PubMed  Google Scholar 

  73. Slentz CA, Duscha BD, Johnson JL, et al. Effects of the amount of exercise on body weight, body composition, and measures of central obesity: STRRIDE-a randomized controlled study. Arch Intern Med. 2004;164:31–9.

    Article  PubMed  Google Scholar 

  74. Lindström J, Louheranta A, Mannelin M, et al. The Finnish Diabetes Prevention Study (DPS): lifestyle intervention and 3-year results on diet and physical activity. Diabetes Care. 2003;26:3230–6.

    Article  PubMed  Google Scholar 

  75. Knowler WC, Barrett-Connor E, Fowler SE, et al. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med. 2002;346:393–403.

    Article  CAS  PubMed  Google Scholar 

  76. Herzig K, Ahola R, Leppäluoto J, et al. Light physical activity determined by a motion sensor decreases insulin resistance, improves lipid homeostasis and reduces visceral fat in high-risk subjects: PreDiabEx study RCT. Int J Obes. 2014;38:1089–96.

    Article  CAS  Google Scholar 

  77. Kim J, Tanabe K, Yokoyama N, et al. Objectively measured light-intensity lifestyle activity and sedentary time are independently associated with metabolic syndrome: a cross-sectional study of Japanese adults. Int J Behav Nutr Phys Act. 2013;10:30.

    Article  PubMed  PubMed Central  Google Scholar 

  78. Scheers T, Philippaerts R, Lefevre J. SenseWear-determined physical activity and sedentary behavior and metabolic syndrome. Med Sci Sports Exerc. 2013;45:481–9.

    Article  PubMed  Google Scholar 

  79. Xu J, Lombardi G, Jiao W, et al. Effects of exercise on bone status in female subjects, from young girls to postmenopausal women: an overview of systematic reviews and meta-analyses. Sports Med. 2016;46:1165–82.

    Article  PubMed  Google Scholar 

  80. Johansson J, Nordström A, Nordström P. Objectively measured physical activity is associated with parameters of bone in 70-year-old men and women. Bone. 2015;81:72–9.

    Article  PubMed  Google Scholar 

  81. Pau M, Leban B, Collu G, et al. Effect of light and vigorous physical activity on balance and gait of older adults. Arch Gerontol Geriatr. 2014;59:568–73.

    Article  PubMed  Google Scholar 

  82. Cooney GM, Dwan K, Greig CA, et al. Exercise for depression. Cochrane Database Syst Rev. 2013;(9):CD004366.

  83. Ensrud KE, Blackwell TL, Cauley JA, et al. Objective measures of activity level and mortality in older men. J Am Geriatr Soc. 2014;62:2079–87.

    Article  PubMed  PubMed Central  Google Scholar 

  84. Hupin D, Roche F, Gremeaux V, et al. Even a low-dose of moderate-to-vigorous physical activity reduces mortality by 22% in adults aged ≥60 years: a systematic review and meta-analysis. Br J Sports Med. 2015;49(19):1262–7.

    Article  PubMed  Google Scholar 

  85. Stensvold D, Nauman J, Nilsen TI, et al. Even low level of physical activity is associated with reduced mortality among people with metabolic syndrome, a population based study (the HUNT 2 study, Norway). BMC Med. 2011;9:109.

    Article  PubMed  PubMed Central  Google Scholar 

  86. Wen CP, Wai JP, Tsai MK, et al. Minimum amount of physical activity for reduced mortality and extended life expectancy: a prospective cohort study. Lancet. 2011;378(9798):1244–53.

    Article  PubMed  Google Scholar 

  87. Achten J, Jeukendrup AE. Effects of pre-exercise ingestion of carbohydrate on glycaemic and insulinaemic responses during subsequent exercise at differing intensities. Eur J Appl Physiol. 2003;88:466–71.

    Article  CAS  PubMed  Google Scholar 

  88. Nygaard H, Tomten SE, Høstmark AT. Slow postmeal walking reduces postprandial glycemia in middle-aged women. Appl Physiol Nutr Metab. 2009;34:1087–92.

    Article  PubMed  Google Scholar 

  89. Kraus WE, Houmard JA, Duscha BD, et al. Effects of the amount and intensity of exercise on plasma lipoproteins. N Engl J Med. 2002;347:1483–92.

    Article  CAS  PubMed  Google Scholar 

  90. Bailey DP, Locke CD. Breaking up prolonged sitting with light-intensity walking improves postprandial glycemia, but breaking up sitting with standing does not. J Sci Med Sport. 2015;18:294–8.

    Article  PubMed  Google Scholar 

  91. Kelly LA, McMillan DG, Anderson A, et al. Validity of actigraphs uniaxial and triaxial accelerometers for assessment of physical activity in adults in laboratory conditions. BMC Med Phys. 2013;13(1):5.

    Article  PubMed  PubMed Central  Google Scholar 

  92. Shiroma EJ, Cook NR, Manson JE, et al. Comparison of self-reported and accelerometer-assessed physical activity in older women. PLoS One. 2015;10:e0145950.

    Article  PubMed  PubMed Central  Google Scholar 

  93. Trost SG, McIver KL, Pate RR. Conducting accelerometer-based activity assessments in field-based research. Med Sci Sports Exerc. 2005;37(11 Suppl):S531–43.

    Article  PubMed  Google Scholar 

  94. Loprinzi PD, Cardinal BJ, Crespo CJ, et al. Differences in demographic, behavioral, and biological variables between those with valid and invalid accelerometry data: implications for generalizability. J Phys Act Health. 2013;10(1):79–84.

    Article  PubMed  Google Scholar 

  95. Brown WJ, Bauman AE, Bull FC, et al. Development of evidence-based physical activity recommendations for adults (18–64 years). Report prepared for the Australian Government Department of Health, August 2012. Available at: http://www.health.gov.au/internet/main/publishing.nsf/Content/health-pubhlth-strateg-phys-act-guidelines/$File/DEB-PAR-Adults-18-64years.pdf.

  96. Colberg SR, Sigal RJ, Yardley JE, et al. Physical activity/exercise and diabetes: a position statement of the American Diabetes Association. Diabetes Care. 2016;39(11):2065–79.

    Article  PubMed  Google Scholar 

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Correspondence to Eszter Füzéki.

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Eszter Füzéki, Tobias Engeroff and Winfried Banzer declare that they have no conflicts of interest relevant to the content of this review.

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Füzéki, E., Engeroff, T. & Banzer, W. Health Benefits of Light-Intensity Physical Activity: A Systematic Review of Accelerometer Data of the National Health and Nutrition Examination Survey (NHANES). Sports Med 47, 1769–1793 (2017). https://doi.org/10.1007/s40279-017-0724-0

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