Sports Medicine

, Volume 47, Issue 9, pp 1769–1793 | Cite as

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

  • Eszter FüzékiEmail author
  • Tobias Engeroff
  • Winfried Banzer
Systematic Review



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


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


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.


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.


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.


Physical Activity Bone Mineral Density Waist Circumference Sedentary Behavior Moderate Quality 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Compliance with Ethical Standards


No sources of funding were used to assist in the preparation of this article.

Conflict of interest

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


  1. 1.
    Booth FW, Roberts CK, Laye MJ. Lack of exercise is a major cause of chronic diseases. Compr Physiol. 2012;2(2):1143–211.PubMedPubMedCentralGoogle Scholar
  2. 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.CrossRefPubMedGoogle Scholar
  3. 3.
    Shephard RJ. Limits to the measurement of habitual physical activity by questionnaires. Br J Sports Med. 2003;37(3):197–206.CrossRefPubMedPubMedCentralGoogle Scholar
  4. 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.CrossRefGoogle Scholar
  5. 5.
    World Health Organization. Global recommendations on physical activity for health. Geneva: World Health Organization; 2010. Available at:
  6. 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.CrossRefPubMedGoogle Scholar
  7. 7.
    Centers for Disease Control and Prevention. National Health and Nutrition Examination Survey. Available from:
  8. 8.
    Centers for Disease Control and Prevention. Key concepts about physical activity monitor data collection methods. Available at:
  9. 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.CrossRefPubMedGoogle Scholar
  10. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  11. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  12. 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.PubMedPubMedCentralGoogle Scholar
  13. 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.CrossRefPubMedGoogle Scholar
  14. 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.CrossRefPubMedGoogle Scholar
  15. 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.CrossRefPubMedGoogle Scholar
  16. 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.CrossRefGoogle Scholar
  17. 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.CrossRefPubMedGoogle Scholar
  18. 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.CrossRefPubMedGoogle Scholar
  19. 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.CrossRefPubMedGoogle Scholar
  20. 20.
    Camhi SM, Sisson SB, Johnson WD, et al. Accelerometer-determined moderate intensity lifestyle activity and cardiometabolic health. Prev Med. 2011;52:358–60.CrossRefPubMedGoogle Scholar
  21. 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.CrossRefPubMedGoogle Scholar
  22. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  23. 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.CrossRefPubMedGoogle Scholar
  24. 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.CrossRefPubMedGoogle Scholar
  25. 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.CrossRefPubMedGoogle Scholar
  26. 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.CrossRefPubMedGoogle Scholar
  27. 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.CrossRefPubMedGoogle Scholar
  28. 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.CrossRefPubMedGoogle Scholar
  29. 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.CrossRefPubMedGoogle Scholar
  30. 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.CrossRefPubMedGoogle Scholar
  31. 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.CrossRefGoogle Scholar
  32. 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.CrossRefPubMedGoogle Scholar
  33. 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.CrossRefPubMedGoogle Scholar
  34. 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.CrossRefPubMedGoogle Scholar
  35. 35.
    Loprinzi PD, Brosky JA Jr. Objectively measured physical activity and balance among U.S. adults. J Strength Cond Res. 2014;28:2290–6.CrossRefPubMedGoogle Scholar
  36. 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.CrossRefPubMedGoogle Scholar
  37. 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.CrossRefPubMedGoogle Scholar
  38. 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.CrossRefPubMedGoogle Scholar
  39. 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.CrossRefPubMedGoogle Scholar
  40. 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.CrossRefPubMedGoogle Scholar
  41. 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.CrossRefPubMedGoogle Scholar
  42. 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.CrossRefPubMedGoogle Scholar
  43. 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.CrossRefPubMedGoogle Scholar
  44. 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.CrossRefPubMedGoogle Scholar
  45. 45.
    Loprinzi PD, Sheffield J, Tyo BM, et al. Accelerometer-determined physical activity, mobility disability, and health. Disabil Health J. 2014;7:419–25.CrossRefPubMedGoogle Scholar
  46. 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.CrossRefPubMedGoogle Scholar
  47. 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.CrossRefGoogle Scholar
  48. 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.CrossRefPubMedGoogle Scholar
  49. 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.CrossRefPubMedGoogle Scholar
  50. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  51. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  52. 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.CrossRefPubMedGoogle Scholar
  53. 53.
    Robson J, Janssen I. Intensity of bouted and sporadic physical activity and the metabolic syndrome in adults. Peer J. 2015;3:e1437.CrossRefPubMedPubMedCentralGoogle Scholar
  54. 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.CrossRefPubMedGoogle Scholar
  55. 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.CrossRefPubMedGoogle Scholar
  56. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  57. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  58. 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. 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.CrossRefPubMedGoogle Scholar
  60. 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.CrossRefPubMedGoogle Scholar
  61. 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.CrossRefPubMedGoogle Scholar
  62. 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.CrossRefPubMedGoogle Scholar
  63. 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.CrossRefPubMedGoogle Scholar
  64. 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.CrossRefPubMedGoogle Scholar
  65. 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.Google Scholar
  66. 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.CrossRefPubMedGoogle Scholar
  67. 67.
    Duncan JJ, Gordon NF, Scott CB. Women walking for health and fitness. How much is enough? JAMA. 1991;266:3295–9.CrossRefPubMedGoogle Scholar
  68. 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.CrossRefPubMedGoogle Scholar
  69. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  70. 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.CrossRefPubMedGoogle Scholar
  71. 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.CrossRefPubMedGoogle Scholar
  72. 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.CrossRefPubMedGoogle Scholar
  73. 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.CrossRefPubMedGoogle Scholar
  74. 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.CrossRefPubMedGoogle Scholar
  75. 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.CrossRefPubMedGoogle Scholar
  76. 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.CrossRefGoogle Scholar
  77. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  78. 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.CrossRefPubMedGoogle Scholar
  79. 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.CrossRefPubMedGoogle Scholar
  80. 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.CrossRefPubMedGoogle Scholar
  81. 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.CrossRefPubMedGoogle Scholar
  82. 82.
    Cooney GM, Dwan K, Greig CA, et al. Exercise for depression. Cochrane Database Syst Rev. 2013;(9):CD004366.Google Scholar
  83. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  84. 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.CrossRefPubMedGoogle Scholar
  85. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  86. 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.CrossRefPubMedGoogle Scholar
  87. 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.CrossRefPubMedGoogle Scholar
  88. 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.CrossRefPubMedGoogle Scholar
  89. 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.CrossRefPubMedGoogle Scholar
  90. 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.CrossRefPubMedGoogle Scholar
  91. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  92. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  93. 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.CrossRefPubMedGoogle Scholar
  94. 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.CrossRefPubMedGoogle Scholar
  95. 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:$File/DEB-PAR-Adults-18-64years.pdf.
  96. 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.CrossRefPubMedGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  • Eszter Füzéki
    • 1
    Email author
  • Tobias Engeroff
    • 1
  • Winfried Banzer
    • 1
  1. 1.Goethe University FrankfurtFrankfurtGermany

Personalised recommendations