Accelerometry and physical activity questionnaires - a systematic review
Open accessAbstract
BACKGROUND: The aim of this study is to review accelerometer wear methods and correlations between accelerometry and physical activity questionnaire data, depending on participant characteristics. METHODS: We included 57 articles about physical activity measurement by accelerometry and questionnaires. Criteria were to have at least 100 participants of at least 18 years of age with manuscripts available in English. Accelerometer wear methods were compared. Spearman and Pearson correlation coefficients between questionnaires and accelerometers and differences between genders, age categories, and body mass index (BMI) categories were assessed. RESULTS: In most investigations, requested wear time was seven days during waking hours and devices were mostly attached on hips with waist belts. A minimum of four valid days with wear time of at least ten hours per day was required in most studies. Correlations (r = Pearson, ρ = Spearman) of total questionnaire scores against accelerometer measures across individual studies ranged from r = 0.08 to ρ = 0.58 (P < 0.001) for men and from r = -0.02 to r = 0.49 (P < 0.01) for women. Correlations for total physical activity among participants with ages ≤65 ranged from r = 0.04 to ρ = 0.47 (P < 0.001) and from r = 0.16 (P = 0.02) to r = 0.53 (P < 0.01) among the elderly (≥65 years). Few studies investigated stratification by BMI, with varying cut points and inconsistent results. CONCLUSION: Accelerometers appear to provide slightly more consistent results in relation to self-reported physical activity among men. Nevertheless, due to overall limited consistency, different aspects measured by each method, and differences in the dimensions studied, it is advised that studies use both questionnaires and accelerometers to gain the most complete physical activity information.
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Both objective and subjective measures of physical activity were used to obtain accurate and complementary data on the effectiveness of the intervention.
“both objective and subjective measures of physical activity were used to obtain accurate and complementary data on the effectiveness of the intervention [42]”
From Feasibility, Usability, and Effectiveness of a Machine Learning–Based Physical Activity Chatbot: Quasi-Experimental Study (2021) · cites this paper as [42]
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Harmon, D. L. (1997) · Atherosclerosis · doi:10.1016/s0021-9150(97)06096-6 · Cited by 16 · see citing works
The Daily Activity Questionnaire
Wollmerstedt, N., Nöth, U. A., Ince, A., Ackermann, H., Martell, J. M., & Hendrich, C. (2009) · The Journal of Arthroplasty · doi:10.1016/j.arth.2009.01.005 · Cited by 16 · see citing works
Mâsse, L. C., Fulton, J. E., Watson, K. B., Tortolero, S. R., Kohl, H. W., Meyers, M. C., Blair, S. N., & Wong, W. W. (2012) · Journal of Physical Activity and Health · doi:10.1123/jpah.9.2.237 · Cited by 8 · see citing works
Hernández-Lougedo, J. (2023) · Springer eBooks · doi:10.1007/978-3-031-26614-0_2 · Cited by 6 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [1]World Health Organization Global recommendations on physical activity for health 2010 Geneva World Health Organization 26180873
Cited by
Sorted by citations
Schuch, F., Vancampfort, D., Firth, J., Rosenbaum, S., Ward, P., Reichert, T., Bagatini, N. C., Bgeginski, R., & Stubbs, B. (2017) · Journal of Affective Disorders · doi:10.1016/j.jad.2016.10.050 · Cited by 663 · see citing works
Direito, A., Carraça, E., Rawstorn, J., Whittaker, R., & Maddison, R. (2017) · Annals of Behavioral Medicine · doi:10.1007/s12160-016-9846-0 · Cited by 337 · see citing works
Barnett, T. A., Kelly, A. S., Young, D. R., Perry, C. K., Pratt, C. A., Edwards, N. M., Rao, G., Vos, M. B., & On behalf of the American Heart Association Obesity Committee of the Council on Lifestyle and Cardiometabolic Health; Council on Cardiovascular Disease in the Young; and Stroke Council (2018) · Circulation · doi:10.1161/cir.0000000000000591 · Cited by 249 · see citing works
Sleep and physical activity in university students: A systematic review and meta-analysis
Memon, A. R., Gupta, C. C., Crowther, M. E., Ferguson, S. A., Tuckwell, G. A., & Vincent, G. E. (2021) · Sleep Medicine Reviews · doi:10.1016/j.smrv.2021.101482 · Cited by 180 · see citing works
Stevens, M. L., Gupta, N., Inan Eroglu, E., Crowley, P. J., Eroglu, B., Bauman, A., Granat, M., Straker, L., Palm, P., Stenholm, S., et al. (2020) · BMJ Open Sport & Exercise Medicine · doi:10.1136/bmjsem-2020-000874 · Cited by 110 · see citing works
Meander, L., Lindqvist, M., Mogren, I., Sandlund, J., West, C. E., & Domellöf, M. (2021) · BMC Pregnancy and Childbirth · doi:10.1186/s12884-021-03627-6 · Cited by 112 · see citing works
Guo, W., Key, T. J., & Reeves, G. K. (2019) · BMJ Open · doi:10.1136/bmjopen-2018-024206 · Cited by 82 · see citing works
To, Q. G., Green, C., & Vandelanotte, C. (2021) · JMIR mHealth and uHealth · doi:10.2196/28577 · Cited by 68 · see citing works
Perry, A. S., Annis, J. S., Master, H., Nayor, M., Hughes, A., Kouame, A., Natarajan, K., Marginean, K., Murthy, V., Roden, D. M., et al. (2023) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgac695 · Cited by 29 · see citing works
- Authors
- Skender, S., Ose, J., Chang-Claude, J., Paskow, M., Brühmann, B., Siegel, E. M., Steindorf, K., & Ulrich, C. M.
- Affiliations
- German Cancer Research Center (DE)
- University of Utah (US)
- Moffitt Cancer Center (US)
- Corresponding author
- Ulrich, Cornelia M.
- ORCID
- Venue
- BMC Public Health
- Published
- 2016-06-16
- Volume
- 16
- Issue
- 1
- Pages
- 515-515
- ISSN
- 1471-2458 (ISSN-L)
- PMC
- PMC4910242
- OpenAlex
- W2426662935
- Cited by
- 449
- References
- 97
- Citations by year
- 2026: 39 · 2025: 63 · 2024: 58 · 2023: 53 · 2022: 51 · 2021: 56 · 2020: 65 · 2019: 33 · 2018: 17 · 2017: 10 · 2016: 4
- FWCI
- 2.55
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- BMC Public Health (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Huntsman Cancer Foundation
- Topics
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Health Sciences › Health Professions › Physical Therapy, Sports Therapy and Rehabilitation › Balance, Gait, and Falls Prevention
- Keywords
- accelerometry, physical activity questionnaire, accelerometer wear time, hip-worn accelerometers, self-reported physical activity, accelerometer validity, sex differences, age differences, body mass index, older adults, physical activity measurement
- MeSH terms
- Humans, Surveys and Questionnaires, Reproducibility of Results, Exercise, Self Report, Accelerometry
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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