{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T19:23:11Z","timestamp":1768418591599,"version":"3.49.0"},"reference-count":42,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2023,8,23]],"date-time":"2023-08-23T00:00:00Z","timestamp":1692748800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000272","name":"National Institute for Health Research","doi-asserted-by":"publisher","award":["16\/41\/04"],"award-info":[{"award-number":["16\/41\/04"]}],"id":[{"id":"10.13039\/501100000272","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Physical activity is increasingly being captured by accelerometers worn on different body locations. The aim of this study was to examine the associations between physical activity volume (average acceleration), intensity (intensity gradient) and cardiometabolic health when assessed by a thigh-worn and wrist-worn accelerometer. A sample of 659 office workers wore an Axivity AX3 on the non-dominant wrist and an activPAL3 micro on the right thigh concurrently for 24 h a day for 8 days. An average acceleration (proxy for physical activity volume) and intensity gradient (intensity distribution) were calculated from both devices using the open-source raw accelerometer processing software GGIR. Clustered cardiometabolic risk (CMR) was calculated using markers of cardiometabolic health, including waist circumference, triglycerides, HDL-cholesterol, mean arterial pressure and fasting glucose. Linear regression analysis assessed the associations between physical activity volume and intensity gradient with cardiometabolic health. Physical activity volume derived from the thigh-worn activPAL and the wrist-worn Axivity were beneficially associated with CMR and the majority of individual health markers, but associations only remained significant after adjusting for physical activity intensity in the thigh-worn activPAL. Physical activity intensity was associated with CMR score and individual health markers when derived from the wrist-worn Axivity, and these associations were independent of volume. Associations between cardiometabolic health and physical activity volume were similarly captured by the thigh-worn activPAL and the wrist-worn Axivity. However, only the wrist-worn Axivity captured aspects of the intensity distribution associated with cardiometabolic health. This may relate to the reduced range of accelerations detected by the thigh-worn activPAL.<\/jats:p>","DOI":"10.3390\/s23177353","type":"journal-article","created":{"date-parts":[[2023,8,23]],"date-time":"2023-08-23T08:57:39Z","timestamp":1692781059000},"page":"7353","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Physical Activity Assessed by Wrist and Thigh Worn Accelerometry and Associations with Cardiometabolic Health"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4503-0479","authenticated-orcid":false,"given":"Benjamin D.","family":"Maylor","sequence":"first","affiliation":[{"name":"Diabetes Research Centre, Population Health Sciences, College of Life Sciences, University of Leicester, Leicester LE1 7RH, UK"},{"name":"Assessment of Movement Behaviours Group (AMBer), Leicester Lifestyle and Health Research Group, Diabetes Research Centre, University of Leicester, Leicester LE1 7RH, UK"},{"name":"Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester LE5 4PW, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Charlotte L.","family":"Edwardson","sequence":"additional","affiliation":[{"name":"Diabetes Research Centre, Population Health Sciences, College of Life Sciences, University of Leicester, Leicester LE1 7RH, UK"},{"name":"Assessment of Movement Behaviours Group (AMBer), Leicester Lifestyle and Health Research Group, Diabetes Research Centre, University of Leicester, Leicester LE1 7RH, UK"},{"name":"Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester LE5 4PW, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9510-7676","authenticated-orcid":false,"given":"Alexandra M.","family":"Clarke-Cornwell","sequence":"additional","affiliation":[{"name":"School of Health and Society, University of Salford, Greater Manchester M5 4WT, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9987-9371","authenticated-orcid":false,"given":"Melanie J.","family":"Davies","sequence":"additional","affiliation":[{"name":"Diabetes Research Centre, Population Health Sciences, College of Life Sciences, University of Leicester, Leicester LE1 7RH, UK"},{"name":"Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester LE5 4PW, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6374-7908","authenticated-orcid":false,"given":"Nathan P.","family":"Dawkins","sequence":"additional","affiliation":[{"name":"Diabetes Research Centre, Population Health Sciences, College of Life Sciences, University of Leicester, Leicester LE1 7RH, UK"},{"name":"Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester LE5 4PW, UK"},{"name":"School of Sport and Wellbeing, Leeds Trinity University, Leeds LS18 5HD, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David W.","family":"Dunstan","sequence":"additional","affiliation":[{"name":"Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia"},{"name":"Institute for Physical Activity and Nutrition, Faculty of Health, Deakin University, Geelong, VIC 3220, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kamlesh","family":"Khunti","sequence":"additional","affiliation":[{"name":"Diabetes Research Centre, Population Health Sciences, College of Life Sciences, University of Leicester, Leicester LE1 7RH, UK"},{"name":"Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester LE5 4PW, UK"},{"name":"NIHR Applied Research Collaboration East Midlands, Diabetes Research Centre, University of Leicester, Leicester LE1 7RH, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tom","family":"Yates","sequence":"additional","affiliation":[{"name":"Diabetes Research Centre, Population Health Sciences, College of Life Sciences, University of Leicester, Leicester LE1 7RH, UK"},{"name":"Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester LE5 4PW, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1463-697X","authenticated-orcid":false,"given":"Alex V.","family":"Rowlands","sequence":"additional","affiliation":[{"name":"Diabetes Research Centre, Population Health Sciences, College of Life Sciences, University of Leicester, Leicester LE1 7RH, UK"},{"name":"Assessment of Movement Behaviours Group (AMBer), Leicester Lifestyle and Health Research Group, Diabetes Research Centre, University of Leicester, Leicester LE1 7RH, UK"},{"name":"Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester LE5 4PW, 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(2017). Large Scale Population Assessment of Physical Activity Using Wrist Worn Accelerometers: The UK Biobank Study. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0169649"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"e179","DOI":"10.1093\/ije\/dyac148","article-title":"Cohort Profile Update: The 1970 British Cohort Study (BCS70)","volume":"52","author":"Sullivan","year":"2022","journal-title":"Int. J. Epidemiol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1019","DOI":"10.1136\/bjsports-2014-093546","article-title":"Evolution of accelerometer methods for physical activity research","volume":"48","author":"Troiano","year":"2014","journal-title":"Br. J. Sports Med."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/j.gaitpost.2022.08.002","article-title":"Validity of the activPAL monitor to measure stepping activity and activity intensity: A systematic review","volume":"97","author":"Wu","year":"2022","journal-title":"Gait Posture"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"298","DOI":"10.3934\/publichealth.2016.2.298","article-title":"Validation and Comparison of Accelerometers Worn on the Hip, Thigh, and Wrists for Measuring Physical Activity and Sedentary Behavior","volume":"3","author":"Montoye","year":"2016","journal-title":"AIMS Public Health"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1123\/jmpb.2019-0052","article-title":"Comparison of Sedentary Time Between Thigh-Worn and Wrist-Worn Accelerometers","volume":"3","author":"Suorsa","year":"2020","journal-title":"J. Meas. Phys. Behav."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"l4570","DOI":"10.1136\/bmj.l4570","article-title":"Dose-response associations between accelerometry measured physical activity and sedentary time and all cause mortality: Systematic review and harmonised meta-analysis","volume":"366","author":"Ekelund","year":"2019","journal-title":"BMJ"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1486","DOI":"10.1093\/gerona\/glaa250","article-title":"Quantifying the Predictive Performance of Objectively Measured Physical Activity on Mortality in the UK Biobank","volume":"76","author":"Leroux","year":"2021","journal-title":"J. Gerontol. A Biol. Sci. Med. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1385","DOI":"10.1038\/s41591-020-1012-3","article-title":"Wearable-device-measured physical activity and future health risk","volume":"26","author":"Strain","year":"2020","journal-title":"Nat. Med."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Klenk, J., Dallmeier, D., Denkinger, M.D., Rapp, K., Koenig, W., Rothenbacher, D., and Acti, F.E.S.G. (2016). Objectively Measured Walking Duration and Sedentary Behaviour and Four-Year Mortality in Older People. PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0153779"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"20578","DOI":"10.1038\/s41598-020-77637-3","article-title":"Both sedentary time and physical activity are associated with cardiometabolic health in overweight adults in a 1 month accelerometer measurement","volume":"10","author":"Sjoros","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Chastin, S.F., Palarea-Albaladejo, J., Dontje, M.L., and Skelton, D.A. (2015). 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, 10.","DOI":"10.1371\/journal.pone.0139984"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"975","DOI":"10.1007\/s00592-018-1161-8","article-title":"Accelerometer-derived physical activity in those with cardio-metabolic disease compared to healthy adults: A UK Biobank study of 52,556 participants","volume":"55","author":"Cassidy","year":"2018","journal-title":"Acta Diabetol."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"De Rooij, B.H., van der Berg, J.D., van der Kallen, C.J., Schram, M.T., Savelberg, H.H., Schaper, N.C., Dagnelie, P.C., Henry, R.M., Kroon, A.A., and Stehouwer, C.D. (2016). Physical Activity and Sedentary Behavior in Metabolically Healthy versus Unhealthy Obese and Non-Obese Individuals\u2014The Maastricht Study. PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0154358"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1080\/02640414.2023.2197726","article-title":"Comparison of physical activity metrics from two research-grade accelerometers worn on the non-dominant wrist and thigh in children","volume":"41","author":"Buchan","year":"2023","journal-title":"J. Sports Sci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1249\/MSS.0000000000002138","article-title":"activPAL and ActiGraph Assessed Sedentary Behavior and Cardiometabolic Health Markers","volume":"52","author":"Edwardson","year":"2020","journal-title":"Med. Sci. Sports Exerc."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"995","DOI":"10.1111\/apa.15043","article-title":"Hip and wrist accelerometers showed consistent associations with fitness and fatness in children aged 8\u201312 years","volume":"109","author":"Leppanen","year":"2020","journal-title":"Acta Paediatr."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2410","DOI":"10.1249\/MSS.0000000000002047","article-title":"Activity Intensity, Volume, and Norms: Utility and Interpretation of Accelerometer Metrics","volume":"51","author":"Rowlands","year":"2019","journal-title":"Med. Sci. Sports Exerc."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1582","DOI":"10.1249\/MSS.0000000000002939","article-title":"Importance of Overall Activity and Intensity of Activity for Cardiometabolic Risk in Those with and Without a Chronic Disease","volume":"54","author":"Dawkins","year":"2022","journal-title":"Med. Sci. Sports Exerc."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1136\/bjsports-2019-100786","article-title":"Emerging collaborative research platforms for the next generation of physical activity, sleep and exercise medicine guidelines: The Prospective Physical Activity, Sitting, and Sleep consortium (ProPASS)","volume":"54","author":"Stamatakis","year":"2020","journal-title":"Br. J. Sports Med."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1816","DOI":"10.1249\/MSS.0000000000000289","article-title":"Age group comparability of raw accelerometer output from wrist- and hip-worn monitors","volume":"46","author":"Hildebrand","year":"2014","journal-title":"Med. Sci. Sports Exerc."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"539","DOI":"10.1123\/jpah.2016-0211","article-title":"Comparison Between Wrist-Worn and Waist-Worn Accelerometry","volume":"14","author":"Loprinzi","year":"2017","journal-title":"J. Phys. Act. Health"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1085","DOI":"10.1249\/MSS.0000000000000865","article-title":"Accuracy of Posture Allocation Algorithms for Thigh- and Waist-Worn Accelerometers","volume":"48","author":"Edwardson","year":"2016","journal-title":"Med. Sci. Sports Exerc."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"e069288","DOI":"10.1136\/bmj-2021-069288","article-title":"Effectiveness of an intervention for reducing sitting time and improving health in office workers: Three arm cluster randomised controlled trial","volume":"378","author":"Edwardson","year":"2022","journal-title":"BMJ"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1177\/0897190016651546","article-title":"Comparing the Accuracy of 2 Point-of-Care Lipid Testing Devices","volume":"30","author":"Bastianelli","year":"2017","journal-title":"J. Pharm. Pract."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.plabm.2017.04.001","article-title":"Comparison of a point-of-care analyser for the determination of HbA1c with HPLC method","volume":"8","author":"Grant","year":"2017","journal-title":"Pract. Lab. Med."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1186\/s12966-018-0748-3","article-title":"Associations of context-specific sitting time with markers of cardiometabolic risk in Australian adults","volume":"15","author":"Dempsey","year":"2018","journal-title":"Int. J. Behav. Nutr. Phys. Act."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2032","DOI":"10.1249\/MSS.0000000000001328","article-title":"A Cluster RCT to Reduce Workers\u2019 Sitting Time: Impact on Cardiometabolic Biomarkers","volume":"49","author":"Healy","year":"2017","journal-title":"Med. Sci. Sports Exerc."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1123\/jmpb.2018-0063","article-title":"GGIR: A Research Community\u2014Driven Open Source R Package for Generating Physical Activity and Sleep Outcomes from Multi-Day Raw Accelerometer Data","volume":"2","author":"Migueles","year":"2019","journal-title":"J. Meas. Phys. Behav."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"738","DOI":"10.1152\/japplphysiol.00421.2014","article-title":"Autocalibration of accelerometer data for free-living physical activity assessment using local gravity and temperature: An evaluation on four continents","volume":"117","author":"Fang","year":"2014","journal-title":"J. Appl. Physiol."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Ricardo, L.I.C., Wendt, A., Galliano, L.M., de Andrade Muller, W., Ni\u00f1o Cruz, G.I., Wehrmeister, F., Brage, S., Ekelund, U., and Crochemore, M.S.I. (2020). Number of days required to estimate physical activity constructs objectively measured in different age groups: Findings from three Brazilian (Pelotas) population-based birth cohorts. PLoS ONE, 15.","DOI":"10.1371\/journal.pone.0216017"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1186\/s40798-019-0225-9","article-title":"Enhancing the value of accelerometer-assessed physical activity: Meaningful visual comparisons of data-driven translational accelerometer metrics","volume":"5","author":"Rowlands","year":"2019","journal-title":"Sports Med. Open"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Kingsnorth, A.P., Rowlands, A.V., Maylor, B.D., Sherar, L.B., Steiner, M.C., Morgan, M.D., Singh, S.J., Esliger, D.W., and Orme, M.W. (2022). A More Intense Examination of the Intensity of Physical Activity in People Living with Chronic Obstructive Pulmonary Disease: Insights from Threshold-Free Markers of Activity Intensity. Int. J. Environ. Res. Public Health, 19.","DOI":"10.3390\/ijerph191912355"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Arvidsson, D., Fridolfsson, J., Buck, C., Ekblom, \u00d6., Ekblom-Bak, E., Lissner, L., Hunsberger, M., and B\u00f6rjesson, M. (2019). Reexamination of Accelerometer Calibration with Energy Expenditure as Criterion: VO2net Instead of MET for Age-Equivalent Physical Activity Intensity. Sensors, 19.","DOI":"10.3390\/s19153377"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Chudasama, Y.V., Khunti, K.K., Zaccardi, F., Rowlands, A.V., Yates, T., Gillies, C.L., Davies, M.J., and Dhalwani, N.N. (2019). Physical activity, multimorbidity, and life expectancy: A UK Biobank longitudinal study. BMC Med., 17.","DOI":"10.1186\/s12916-019-1339-0"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1186\/s40798-022-00541-9","article-title":"Associations Between Wearable-Specific Indicators of Physical Activity Behaviour and Insulin Sensitivity and Glycated Haemoglobin in the General Population: Results from the ORISCAV-LUX 2 Study","volume":"8","author":"Backes","year":"2022","journal-title":"Sports Med. Open"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1038\/s41366-021-00970-8","article-title":"Joint associations between objectively measured physical activity volume and intensity with body fatness: The Fenland study","volume":"46","author":"Lindsay","year":"2022","journal-title":"Int. J. Obes."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1249\/MSS.0000000000001100","article-title":"Step-Based Physical Activity Metrics and Cardiometabolic Risk: NHANES 2005\u20132006","volume":"49","author":"Schuna","year":"2017","journal-title":"Med. Sci. Sports Exerc."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Lu, Y., Wiltshire, H.D., Baker, J.S., Wang, Q., Ying, S., Li, J., and Lu, Y. (2022). Associations between Objectively Determined Physical Activity and Cardiometabolic Health in Adult Women: A Systematic Review and Meta-Analysis. Biology, 11.","DOI":"10.3390\/biology11060925"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"298","DOI":"10.1123\/jmpb.2020-0061","article-title":"Impact of Reduced Sampling Rate on Accelerometer-Based Physical Activity Monitoring and Machine Learning Activity Classification","volume":"4","author":"Small","year":"2021","journal-title":"J. Meas. Phys. Behav."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1769","DOI":"10.1007\/s40279-017-0724-0","article-title":"Health Benefits of Light-Intensity Physical Activity: A Systematic Review of Accelerometer Data of the National Health and Nutrition Examination Survey (NHANES)","volume":"47","author":"Fuzeki","year":"2017","journal-title":"Sports Med."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1151","DOI":"10.1001\/jama.2020.1382","article-title":"Association of Daily Step Count and Step Intensity with Mortality among US Adults","volume":"323","author":"Troiano","year":"2020","journal-title":"JAMA"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/17\/7353\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T20:41:03Z","timestamp":1760128863000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/17\/7353"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,23]]},"references-count":42,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2023,9]]}},"alternative-id":["s23177353"],"URL":"https:\/\/doi.org\/10.3390\/s23177353","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,23]]}}}