Skip to content

Publication list

Jump to bottom
Matt Patterson edited this page Aug 24, 2021 · 122 revisions

Peer-reviewed academic publications using GGIR:

This is a non-exhaustive list, and mostly limited to publications for which we could check that GGIR was used. Occassionally we come across publications where authors do not cite the GGIR software when GGIR is used. Software citation is important for making the research reproducible and to give credit to the efforts that goes into the development and maintainance of Open Source software.

Please cite the following paper in your work if using GGIR: Migueles, J.H., Rowlands, A.V., Huber, F., Sabia, S. and van Hees, V.T., 2019. GGIR: a research community–driven open source R package for generating physical activity and sleep outcomes from multi-day raw accelerometer data. Journal for the Measurement of Physical Behaviour, 2(3), pp.188-196.

2021

  1. McDonough, D.J., Helgeson, M.A., Liu, W. and Gao, Z., 2021. Effects of a remote, YouTube-delivered exercise intervention on young adults’ physical activity, sedentary behavior, and sleep during the COVID-19 pandemic: Randomized controlled trial. Journal of Sport and Health Science.
  2. Sherry, A.P., Clemes, S.A., Chen, Y.L., Edwardson, C., Gray, L.J., Guest, A., King, J., Rowlands, A.V., Ruettger, K., Sayyah, M. and Varela-Mato, V., 2021. Sleep duration and sleep efficiency in UK long-distance heavy goods vehicle drivers. Occupational and Environmental Medicine.
  3. Stone, J.E., Phillips, A.J., Chachos, E., Hand, A.J., Lu, S., Carskadon, M.A., Klerman, E.B., Lockley, S.W., Wiley, J.F., Bei, B. and Rajaratnam, S.M., 2021. In‐person vs. home schooling during the COVID‐19 pandemic: Differences in sleep, circadian timing, and mood in early adolescence. Journal of Pineal Research, p.e12757.
  4. Yerramalla, M.S., McGregor, D.E., van Hees, V.T., Fayosse, A., Dugravot, A., Tabak, A.G., Chen, M., Chastin, S.F. and Sabia, S., 2021. Association of daily composition of physical activity and sedentary behaviour with incidence of cardiovascular disease in older adults. International Journal of Behavioral Nutrition and Physical Activity, 18(1), pp.1-13.
  5. Williams, R.A., 2021. Effect of physical activity and fitness on risk factors for cardiometabolic disease and cognitive function in adolescents (Doctoral dissertation, Nottingham Trent University).
  6. Van Cappellen-van Maldegem, S.J., Mols, F., Horevoorts, N., De Kruif, A., Buffart, L.M., Schoormans, D., Trompetter, H., Beijer, S., Ezendam, N.P., De Boer, M. and Winkels, R., 2021. Towards OPtimal TIming and Method for promoting sUstained adherence to lifestyle and body weight recommendations in postMenopausal breast cancer survivors (the OPTIMUM-study): protocol for a longitudinal mixed-method study. BMC women's health, 21(1), pp.1-14.
  7. Liu, F., Wanigatunga, A.A. and Schrack, J.A., 2021. Assessment of Physical Activity in Adults using Wrist Accelerometers. Epidemiologic Reviews.
  8. Malheiros, L.E., da Costa, B.G., Lopes, M.V. and Silva, K.S., 2021. School schedule affects sleep, but not physical activity, screen time and diet behaviors. Sleep Medicine, 85, pp.54-59.
  9. Thomson, N.K., Albrecht, B.M., Buchan, D.S. and Easton, C., 2021. Generation and validation of ActiGraph GT3X+ accelerometer cut-points for assessing physical activity intensity in older adults. The OUTDOOR ACTIVE validation study.
  10. Edwardson, C.L., Maylor, B.D., Dawkins, N.P., Plekhanova, T. and Rowlands, A.V., 2021. Comparability of Postural and Physical Activity Metrics from Different Accelerometer Brands Worn on the Thigh: Data Harmonization Possibilities. Measurement in Physical Education and Exercise Science, pp.1-12.
  11. Dygrýn, J., Medrano, M., Molina-Garcia, P., Rubín, L., Jakubec, L., Janda, D. and Gába, A., 2021. Associations of novel 24-h accelerometer-derived metrics with adiposity in children and adolescents. Environmental Health and Preventive Medicine, 26(1), pp.1-8.
  12. Fernández-Verdejo, R., Alcantara, J.M., Galgani, J.E., Acosta, F.M., Migueles, J.H., Amaro-Gahete, F.J., Labayen, I., Ortega, F.B. and Ruiz, J.R., 2021. Deciphering the constrained total energy expenditure model in humans by associating accelerometer-measured physical activity from wrist and hip. Scientific reports, 11(1), pp.1-10.
  13. Antczak, D., Lonsdale, C., del Pozo Cruz, B., Parker, P. and Sanders, T., 2021. Reliability of GENEActiv accelerometers to estimate sleep, physical activity, and sedentary time in children. International Journal of Behavioral Nutrition and Physical Activity, 18(1), pp.1-11.
  14. Zhang, X., Shen, H. and Lv, Z., 2021. Deployment optimization of multi-stage investment portfolio service and hybrid intelligent algorithm under edge computing. Plos one, 16(6), p.e0252244.
  15. Nikbakhtian, S., Reed, A.B., Obika, B.D., Morelli, D., Cunningham, A.C., Aral, M. and Plans, D., Accelerometer-Derived Sleep Onset Timing and Cardiovascular Disease Incidence: A UK Biobank Cohort Study. Available at SSRN 3857637.
  16. Buman, M., 2021. Rachel Crosley Lyons (Doctoral dissertation, ARIZONA STATE UNIVERSITY).
  17. Gill, G. and Patterson, M.R., Verisense Validation According to the V3 Validation Framework.
  18. Bammann, K., Thomson, N.K., Albrecht, B.M., Buchan, D.S. and Easton, C., 2021. Generation and validation of ActiGraph GT3X+ accelerometer cut-points for assessing physical activity intensity in older adults. The OUTDOOR ACTIVE validation study. PloS one, 16(6), p.e0252615.
  19. Aguayo, G.A., Pastore, J., Backes, A., Stranges, S., Witte, D.R., Diederich, N.J., Alkerwi, A.A., Huiart, L., Ruiz-Castell, M., Malisoux, L. and Fagherazzi, G., 2021. Objective and subjective sleep measures are associated with HbA1c and insulin sensitivity in the general population: Findings from the ORISCAV-LUX-2 study. Diabetes & Metabolism, p.101263.
  20. da Costa, B.G.G., Chaput, J.P., Lopes, M.V.V., Gaya, A.R., Silva, D.A.S. and Silva, K.S., 2021. Association between sociodemographic, dietary, and substance use factors and accelerometer-measured 24-hour movement behaviours in Brazilian adolescents. European Journal of Pediatrics, pp.1-9.
  21. Ormel, H.L., Schröder, C.P., van der Schoot, G.G., Westerink, N.D.L., van der Velden, A.W., Poppema, B., Vrieling, A.H., Gietema, J.A., Walenkamp, A.M. and Reyners, A.K., 2021. Effects of supervised exercise during adjuvant endocrine therapy in overweight or obese patients with breast cancer: The I-MOVE study. The Breast, 58, pp.138-146.
  22. Zamora, A.N., Arboleda-Merino, L., Tellez-Rojo, M.M., O’Brien, L.M., Torres-Olascoaga, L.A., Peterson, K.E., Banker, M., Fossee, E., Song, P.X., Taylor, K. and Cantoral, A., 2021. Sleep Difficulties among Mexican Adolescents: Subjective and Objective Assessments of Sleep. Behavioral Sleep Medicine, pp.1-15.
  23. Mielke, G.I., Menezes, A.M., da Silva, B.G.C., Ekelund, U., Crochemore-Silva, I., Wehrmeister, F.C., Gonçalves, H. and Brown, W.J., 2021. Associations between Device-measured Physical Activity and Cardiometabolic Health in the Transition to Early Adulthood. Medicine and Science in Sports and Exercise.
  24. Stewart, M.T., Nezich, T., Lee, J.M., Hasson, R.E. and Colabianchi, N., 2021. Using a Mobile Phone App to Analyze the Relationship Between Planned and Performed Physical Activity in University Students: Observational Study. JMIR mHealth and uHealth, 9(4), p.e17581.
  25. Smith, R.W., Harty, P.S., Stratton, M.T., Rafi, Z., Rodriguez, C., Dellinger, J.R., Benavides, M.L., Johnson, B.A., White, S.J., Williams, A.D. and Tinsley, G.M., 2021. Predicting Adaptations to Resistance Training Plus Overfeeding Using Bayesian Regression: A Preliminary Investigation. Journal of Functional Morphology and Kinesiology, 6(2), p.36.
  26. Lee, P.M.Y., Kwok, B.H.L., Ma, J.Y.T. and Tse, L.A., 2021. A population-based prospective study on rest-activity rhythm and mild cognitive impairment among Hong Kong healthy community-dwelling older adults. Neurobiology of Sleep and Circadian Rhythms, 10, p.100065.
  27. Suorsa, K., Leskinen, T., Pulakka, A., Pentti, J., Löyttyniemi, E., Heinonen, I., Vahtera, J. and Stenholm, S., 2021. The effect of a consumer-based activity tracker intervention on accelerometer-measured sedentary time among retirees: a randomized controlled REACT trial. The Journals of Gerontology: Series A.
  28. Gilson, N.D., Mielke, G.I., Coombes, J.S., Feter, N., Smith, E., Duncan, M.J., Wallis, G. and Brown, W.J., 2021. VO2peak and 24‐hour sleep, sedentary behavior, and physical activity in Australian truck drivers. Scandinavian Journal of Medicine & Science in Sports.
  29. Argyridou, S., Davies, M.J., Biddle, G.J., Bernieh, D., Suzuki, T., Dawkins, N.P., Rowlands, A.V., Khunti, K., Smith, A.C. and Yates, T., 2021. Evaluation of an 8-Week Vegan Diet on Plasma Trimethylamine-N-Oxide and Postchallenge Glucose in Adults with Dysglycemia or Obesity. The Journal of Nutrition.
  30. Chong, K.H., Parrish, A.M., Cliff, D.P., Dumuid, D. and Okely, A.D., 2021. Changes in 24-hour movement behaviours during the transition from primary to secondary school among Australian children. European Journal of Sport Science, pp.1-11.
  31. Vetrovsky, T., Omcirk, D., Malecek, J., Stastny, P., Steffl, M. and Tufano, J.J., 2021. Morning fatigue and structured exercise interact to affect non-exercise physical activity of fit and healthy older adults. BMC geriatrics, 21(1), pp.1-10.
  32. Sandborg, J., Söderström, E., Henriksson, P., Bendtsen, M., Henström, M., Leppänen, M.H., Maddison, R., Migueles, J.H., Blomberg, M. and Löf, M., 2021. Effectiveness of a Smartphone App to Promote Healthy Weight Gain, Diet, and Physical Activity During Pregnancy (HealthyMoms): Randomized Controlled Trial. JMIR mHealth and uHealth, 9(3), p.e26091.
  33. Rowlands, A.V., Henson, J.J., Coull, N.A., Edwardson, C.L., Brady, E., Hall, A., Khunti, K., Davies, M. and Yates, T., 2021. The impact of COVID‐19 restrictions on accelerometer‐assessed physical activity and sleep in individuals with type 2 diabetes. Diabetic Medicine, p.e14549.
  34. Pasanen, J., 2021. Compositional data analysis applied to a study of movement behaviours of recent retirees.
  35. Lucia, S., Effects of the Active Choices Program on Self-Managed Physical Activity and Social Connectedness in Australian Defence Force Veterans: Protocol for a Cluster-Randomized Trial.
  36. Aguilar-Farias, N., Miranda-Marquez, S., Toledo-Vargas, M. and Chandia-Poblete, D., Imprimir ARTIGO: Comparação de autorrelato e medidas derivadas de acelerômetro para classificar a atividade física em crianças e adolescentes chilenos.
  37. Aguilar-Farias, N., Miranda-Marquez, S., Toledo-Vargas, M. and Chandia-Poblete, D., 2021. Comparison between self-reported and accelerometer-derived measurements for classifying children and adolescents as physically active in Chile. Cadernos de Saúde Pública, 37, p.e00240620.
  38. Harrington, D.M., Ioannidou, E., Davies, M.J., Edwardson, C.L., Gorely, T., Rowlands, A.V., Sherar, L.B. and Staiano, A.E., 2021. Concurrent screen use and cross‐sectional association with lifestyle behaviours and psychosocial health in adolescent females. Acta Paediatrica.
  39. Leskinen, T., Suorsa, K., Tuominen, M., Pulakka, A., Pentti, J., Löyttyniemi, E., Heinonen, I., Vahtera, J. and Stenholm, S., 2021. The effect of consumer-based activity tracker intervention on physical activity among recent retirees—an RCT study. Medicine and science in sports and exercise, 53(8), p.1756.
  40. Prasad, S., Ramanan, D., Bennani, H., Paulin, M., Cannon, R.D., Palla, S. and Farella, M., 2021. Associations among masticatory muscle activity, physical activity and self-reported oral behaviours in adult women. Clinical Oral Investigations, pp.1-11.
  41. Alonso-Martínez, A.M., Ramírez-Vélez, R., García-Alonso, Y., Izquierdo, M. and García-Hermoso, A., 2021. Physical activity, sedentary behavior, sleep and self-regulation in Spanish preschoolers during the COVID-19 lockdown. International Journal of Environmental Research and Public Health, 18(2), p.693.
  42. Migueles, J.H., Aadland, E., Andersen, L.B., Brønd, J.C., Chastin, S.F., Hansen, B.H., Konstabel, K., Kvalheim, O.M., McGregor, D.E., Rowlands, A.V. and Sabia, S., 2021. GRANADA consensus on analytical approaches to assess associations with accelerometer-determined physical behaviours (physical activity, sedentary behaviour and sleep) in epidemiological studies. British Journal of Sports Medicine.
  43. Kuzik, N., Spence, J.C. and Carson, V., 2021. Machine learning sleep duration classification in Preschoolers using waist-worn ActiGraphs. Sleep Medicine, 78, pp.141-148.
  44. Sundararajan, K., Georgievska, S., Te Lindert, B.H., Gehrman, P.R., Ramautar, J., Mazzotti, D.R., Sabia, S., Weedon, M.N., van Someren, E.J., Ridder, L. and Wang, J., 2021. Sleep classification from wrist-worn accelerometer data using random forests. Scientific reports, 11(1), pp.1-10.
  45. Vallarta-Robledo, J.R., Joost, S., Ruas, M.A.V., Gubelmann, C., Vollenweider, P., Marques-Vidal, P. and Guessous, I., 2021. Geographic clusters of objectively measured physical activity and the characteristics of their built environment in a Swiss urban area. medRxiv.
  46. Sanchez-Flack, J.C., Tussing-Humphreys, L., Lamar, M., Fantuzzi, G., Schiffer, L., Blumstein, L., McLeod, A., Dakers, R., Strahan, D., Restrepo, L. and Hemphill, N.O.N., 2021. Building research in diet and cognition (BRIDGE): baseline characteristics of older obese African American adults in a randomized controlled trial to examine the effect of the Mediterranean diet with and without weight loss on cognitive functioning. Preventive Medicine Reports, 22, p.101302.
  47. McDevitt, B., Moore, L., Akhtar, N., Connolly, J., Doherty, R. and Scott, W., 2021. Validity of a Novel Research-Grade Physical Activity and Sleep Monitor for Continuous Remote Patient Monitoring. Sensors, 21(6), p.2034.
  48. Johnson, N.R., Kotarsky, C.J., Hackney, K.J., Trautman, K.A., Dicks, N.D., Byun, W., Keith, J.F., David, S.L. and Stastny, S.N., 2021. Measures Derived from Panoramic Ultrasonography and Animal-Based Protein Intake Are Related to Muscular Performance in Middle-Aged Adults. Journal of clinical medicine, 10(5), p.988.
  49. Chong, K.H., Parrish, A.M., Cliff, D.P., Dumuid, D. and Okely, A.D., 2021. Cross-Sectional and Longitudinal Associations between 24-Hour Movement Behaviours, Recreational Screen Use and Psychosocial Health Outcomes in Children: A Compositional Data Analysis Approach. International Journal of Environmental Research and Public Health, 18(11), p.5995.
  50. Migueles, J.H., Cadenas-Sanchez, C., Alcantara, J., Leal-Martín, J., Mañas, A., Ara, I., Glynn, N.W. and Shiroma, E.J., 2021. Calibration and Cross-Validation of Accelerometer Cut-Points to Classify Sedentary Time and Physical Activity from Hip and Non-Dominant and Dominant Wrists in Older Adults. Sensors, 21(10), p.3326.
  51. Longman, D.P., Shaw, C.N., Varela-Mato, V., Sherry, A.P., Ruettger, K., Sayyah, M., Guest, A., Chen, Y.L., Paine, N.J., King, J.A. and Clemes, S.A., 2021. Time in nature associated with decreased fatigue in UK truck drivers. International journal of environmental research and public health, 18(6), p.3158.
  52. Llamocca, P., López, V., Santos, M. and Čukić, M., 2021. Personalized Characterization of Emotional States in Patients with Bipolar Disorder. Mathematics, 9(11), p.1174.
  53. Gilson, N.D., Papinczak, Z.E., Mielke, G.I., Haslam, C., Fooken, J., McKenna, J. and Brown, W.J., 2021. Effects of the Active Choices Program on Self-Managed Physical Activity and Social Connectedness in Australian Defence Force Veterans: Protocol for a Cluster-Randomized Trial. JMIR research protocols, 10(2), p.e21911.
  54. Pollard, B., Engelen, L., Held, F. and de Dear, R., 2021. Movement at work: A comparison of real time location system, accelerometer and observational data from an office work environment. Applied Ergonomics, 92, p.103341.
  55. del Pozo Cruz, B., Hartwig, T.B., Sanders, T., Noetel, M., Parker, P., Antczak, D., Lee, J., Lubans, D.R., Bauman, A., Cerin, E. and Lonsdale, C., 2021. The effects of the Australian bushfires on physical activity in children. Environment International, 146, p.106214.
  56. Ratcliffe, A.M., Zhai, B., Guan, Y., Jackson, D.G., South West Anaesthesia Research Matrix (SWARM), Sneyd, J.R., Minto, G., Howell, S., Miller, F., Retief, J.L. and Webster, D.A., 2021. Patient‐centred measurement of recovery from day‐case surgery using wrist worn accelerometers: a pilot and feasibility study. Anaesthesia, 76(6), pp.785-797.
  57. Antczak, D., Sanders, T., del Pozo Cruz, B., Parker, P. and Lonsdale, C., 2021. Day-to-day and longer-term longitudinal associations between physical activity, sedentary behavior, and sleep in children. Sleep, 44(4), p.zsaa219.
  58. Mickute, M., Henson, J., Rowlands, A.V., Sargeant, J.A., Webb, D., Hall, A.P., Edwardson, C.L., Baldry, E.L., Brady, E.M., Khunti, K. and Davies, M.J., 2021. Device‐measured physical activity and its association with physical function in adults with type 2 diabetes mellitus. Diabetic Medicine, 38(6), p.e14393.
  59. Dawkins, N.P., Yates, T., Edwardson, C.L., Maylor, B., Davies, M.J., Dunstan, D., Highton, P.J., Herring, L.Y., Khunti, K. and Rowlands, A.V., 2021. Comparing 24 h physical activity profiles: Office workers, women with a history of gestational diabetes and people with chronic disease condition (s). Journal of Sports Sciences, 39(2), pp.219-226.
  60. Richer, R., Küderle, A., Dörr, J., Rohleder, N. and Eskofier, B.M., 2021, July. Assessing the Influence of the Inner Clock on the Cortisol Awakening Response and Pre-Awakening Movement. In 2021 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI) (pp. 1-4). IEEE.
  61. Hofman, A., Voortman, T., Ikram, M.A. and Luik, A.I., 2021. Substitutions of physical activity, sedentary behaviour and sleep: associations with mental health in middle-aged and elderly persons. J Epidemiol Community Health.
  62. He, L., Zhao, W., Gao, Y., Gao, X. and Lei, X., 2021. The effect of COVID-19 lockdowns on sleep time perception: Comparing actigraphy and sleep diary measures. International Journal of Psychophysiology, 167, pp.86-93.
  63. Berry, A., Drake, R.J., Butcher, I. and Yung, A.R., 2021. Examining the feasibility, acceptability, validity and reliability of physical activity, sedentary behaviour and sleep measures in people with schizophrenia. Mental Health and Physical Activity, 21, p.100415.
  64. Jenkins, C.A., Tiley, L.C., Lay, I., Hartmann, J.A., Chan, J.K. and Nicholas, C.L., 2021. Comparing GENEActiv against Actiwatch-2 over Seven Nights Using a Common Sleep Scoring Algorithm and Device-Specific Wake Thresholds. Behavioral Sleep Medicine, pp.1-11.
  65. McDonnell, E.I., Zipunnikov, V., Schrack, J.A., Goldsmith, J. and Wrobel, J., 2021. Registration of 24-hour accelerometric rest-activity profiles and its application to human chronotypes. Biological Rhythm Research, pp.1-21.
  66. Nichles, A., Zmicerevska, N., Song, Y.J.C., Wilson, C., McHugh, C., Hamilton, B., Crouse, J., Rohleder, C., Carpenter, J.S., Ho, N. and Hermens, D.F., 2021. Neurobiology Youth Follow-up Study: protocol to establish a longitudinal and prospective research database using multimodal assessments for current and past mental health treatment-seeking young people within an early intervention service. BMJ open, 11(6), p.e044731.
  67. Wilson, C., Nichles, A., Zmicerevska, N., Carpenter, J.S., Song, Y.J.C., McHugh, C., Hamilton, B., Hockey, S., Scott, E.M. and Hickie, I.B., 2021. Effect of an online healthy lifestyle psychoeducation programme to improve cardiometabolic outcomes and affective symptoms in youth receiving mental health care: study protocol for a pilot clinical trial. BMJ open, 11(6), p.e044977.
  68. Husu, P., Tokola, K., Vähä-Ypyä, H., Sievänen, H., Suni, J., Heinonen, O.J., Heiskanen, J., Kaikkonen, K.M., Savonen, K., Kokko, S. and Vasankari, T., 2021. Physical Activity, Sedentary Behavior, and Time in Bed Among Finnish Adults Measured 24/7 by Triaxial Accelerometry. Journal for the Measurement of Physical Behaviour, 4(2), pp.163-173.
  69. Fenton, S., Burrows, T.L., Collins, C.E., Holliday, E.G., Kolt, G.S., Murawski, B., Rayward, A.T., Stamatakis, E., Vandelanotte, C. and Duncan, M.J., 2021. Behavioural mediators of reduced energy intake in a physical activity, diet, and sleep behaviour weight loss intervention in adults. Appetite, 165, p.105273.
  70. Suorsa, K. "SEDENTARY TIME ACROSS THE TRANSITION TO RETIREMENT AND AFTER AN ACTIVITY TRACKER INTERVENTION." Thesis. Turun Yliopisto University of Turku 2021.
  71. Sabia, S., Fayosse, A., Dumurgier, J., van Hees, V.T., Paquet, C., Sommerlad, A., Kivimäki, M., Dugravot, A. and Singh-Manoux, A., 2021. Association of sleep duration in middle and old age with incidence of dementia. Nature Communications, 12(1), pp.1-10.
  72. Leroux, A., Rzasa-Lynn, R., Crainiceanu, C. and Sharma, T., 2021. Wearable Devices: Current Status and Opportunities in Pain Assessment and Management. Digital Biomarkers, 5(1), pp.89-102.
  73. Fischer, D., Klerman, E.B. and Phillips, A.J., 2021. Measuring sleep regularity: Theoretical properties and practical usage of existing metrics. Sleep.
  74. Gucciardi, D.F., Lang, J.W., Lines, R.L., Chapman, M.T., Ducker, K.J., Peeling, P., Crane, M., Ntoumanis, N., Parker, S.K., Thøgersen-Ntoumani, C. and Quested, E., 2021. The emergence of resilience: Recovery trajectories in sleep functioning after a major stressor. Sport, Exercise, and Performance Psychology.
  75. Ng, E., Wake, M., Olds, T., Lycett, K., Edwards, B., Le, H. and Dumuid, D., 2021. Equivalence curves for healthy lifestyle choices. Pediatrics, 147(4).
  76. Arias-Tellez, M.J., Acosta, F.M., Migueles, J.H., Pascual-Gamarra, J.M., Merchan-Ramirez, E., de Lucena Martins, C.M., Llamas-Elvira, J.M., Martinez-Tellez, B. and Ruiz, J.R., 2021. Higher Physical Activity Is Related to Lower Neck Adiposity in Young Men, but to Higher Neck Adiposity in Young Women: An Exploratory Study. International Journal of Sport Nutrition and Exercise Metabolism, 31(3), pp.250-258.
  77. Bourdillon, N., Jeanneret, F., Nilchian, M., Albertoni, P., Ha, P. and Millet, G.P., 2021. Sleep Deprivation Deteriorates Heart Rate Variability and Photoplethysmography. Frontiers in Neuroscience, 15, p.310.
  78. Lane, J.M., Jones, S., Dashti, H.S., Wood, A.R., Aragam, K., van Hees, V.T., Brumpton, B., Winsvold, B., Wang, H., Bowden, J. and Song, Y., Biological and clinical insights from genetics of insomnia symptoms Short Title: Insights from genetics of insomnia symptoms.
  79. Urgelés Puértolas, Diego. "Predicción del estado afectivo en el trastorno bipolar." Tesis Doctoral. Universidad Complutense de Madrid (2021).
  80. Matricciani, L., Paquet, C., Fraysse, F., Grobler, A., Wang, Y., Baur, L., Juonala, M., Nguyen, M.T., Ranganathan, S., Burgner, D. and Wake, M., 2021. Sleep and cardiometabolic risk: a cluster analysis of actigraphy-derived sleep profiles in adults and children. Sleep.
  81. Tracy, J.D., Donnelly, T., Sommer, E.C., Heerman, W.J., Barkin, S.L. and Buchowski, M.S., 2021. Identifying bedrest using waist-worn triaxial accelerometers in preschool children. PloS one, 16(1), p.e0246055.
  82. Dumuid, D., Wake, M., Burgner, D., Tremblay, M.S., Okely, A.D., Edwards, B., Dwyer, T. and Olds, T., 2021. Balancing time use for children’s fitness and adiposity: Evidence to inform 24-hour guidelines for sleep, sedentary time and physical activity. Plos one, 16(1), p.e0245501.
  83. Smith, A.E., Wade, A.T., Olds, T.S., Dumuid, D., Breakspear, M.J., Laver, K.E., Goldsworthy, M.R., Ridding, M.C., Fabiani, M., Dorrian, J. and McKewen, M., 2021. Optimising activity and diet compositions for dementia prevention: Protocol for the ACTIVate prospective longitudinal cohort study. medRxiv.
  84. Watson, A., Dumuid, D., Maher, C. and Olds, T., 2021. Associations between meeting 24-hour movement guidelines and academic achievement in Australian primary school-aged children. Journal of Sport and Health Science.
  85. Flanagan, E.W., Most, J., Broskey, N.T., Altazan, A.D., Beyl, R.A., Keadle, S.K., Drews, K.L., Singh, P. and Redman, L.M., 2021. Identification of changes in sleep across pregnancy and the impact on cardiometabolic health and energy intake in women with obesity. Sleep Medicine, 77, pp.120-127.
  86. Marshall, Z.A., Mackintosh, K.A., Lewis, M.J., Ellins, E.A. and McNarry, M.A., 2021. Association of physical activity metrics with indicators of cardiovascular function and control in children with and without type 1 diabetes. Pediatric Diabetes, 22(2), pp.320-328.
  87. Antczak, D., Sanders, T., del Pozo Cruz, B., Parker, P. and Lonsdale, C., 2021. Day-to-day and longer-term longitudinal associations between physical activity, sedentary behavior, and sleep in children. Sleep, 44(4), p.zsaa219.
  88. Smith, E., Fazeli, F., Wilkinson, K. and Clark, C.C., 2021. Physical behaviors and fundamental movement skills in British and Iranian children: An isotemporal substitution analysis. Scandinavian Journal of Medicine & Science in Sports, 31(2), pp.398-404.

2020

  1. Cadenas-Sanchez C. Migueles JH, et al. Fitness, physical activity and academic achievement in overweight/obese children. Physical Activity, Health and Exercise 2020. doi: 10.1080/02640414.2020.1729516
  2. Jurado‐Fasol L, De-la-O A, et al. Exercise training improves sleep quality: A randomized controlled trial. Eur J of Clin Investigation 2020. doi: 10.1111/eci.13202
  3. Chen B, Bernard JY et al. Associations between early-life screen viewing and 24 hour movement behaviours: findings from a longitudinal birth cohort study. The Lancet Child & Adolescent Health 2020. doi: 10.1016/S2352-4642(19)30424-9
  4. Ding D, Mielke GI, et al. Prenatal and birth predictors of objectively measured physical activity and sedentary time in three population-based birth cohorts in Brazil. Scientific Reports 2020. doi: 10.1038/s41598-019-57070-x
  5. Novak B, Holler P, et al. Do we have to reduce the recall period? Validity of a daily physical activity questionnaire (PAQ24) in young active adults. BMC Public Health 2020. doi: 10.1186/s12889-020-8165-3
  6. Hamer M, Patalay P, et al. Change in device-measured physical activity assessed in childhood and adolescence in relation to depressive symptoms: a general population-based cohort study. J of Epi & Community Health. 2020. doi: 10.1136/jech-2019-213399
  7. Cadenas-Sanchez C., Esteban-Cornejo I, et al. Twenty four‐hour activity cycle in older adults using wrist‐worn accelerometers: The seniors‐ENRICA‐2 study. SJMSS. 2020. doi: 10.1111/sms.13612
  8. Troxel WM, Haas A, et al. Broken Windows, Broken Zzs: Poor Housing and Neighborhood Conditions Are Associated with Objective Measures of Sleep Health. Journal of Urban Health 2020. doi: 10.1007/s11524-019-00418-5
  9. Amaro‐Gahete FJ, Acosta FM, et al. Association of sedentary and physical activity time with maximal fat oxidation during exercise in sedentary adults, Scan J of Med Science in Sports 2020 doi: 10.1111/sms.13696
  10. Amaro‐Gahete FJ, Jurado-Fasoli L, et al. Association of Basal Metabolic Rate and Nutrients Oxidation with Cardiometabolic Risk Factors and Insulin Sensitivity in Sedentary Middle-Aged Adults. Nutriens 2020, doi: 10.3390/nu12041186
  11. Migueles JH, Cadenas-Sanchez C, et al. Associations of Objectively-Assessed Physical Activity and Sedentary Time with Hippocampal Gray Matter Volume in Children with Overweight/Obesity. Clinical Medicine 2020. doi: 10.3390/jcm9041080
  12. Mora-Gonzalez J, Esteban-Cornejo I, et al. Fitness, physical activity, sedentary time, inhibitory control, and neuroelectric activity in children with overweight or obesity: The ActiveBrains project. Psychophysiology 2020. doi: 10.1111/psyp.13579.
  13. Garcia-Hermoso A, Hormazabal-Auayo I, et al. Exercise program and blood pressure in children: The moderating role of sedentary time. J of Science and Med in Sport. 2020. doi: 10.1016/j.jsams.2020.02.012
  14. Matricciani L, Paquet C, et al. Sleep profiles of Australian children aged 11-12 years and their parents: sociodemographic characteristics and lifestyle correlates. Sleep Medicine. 2020. doi: 10.1016/j.sleep.2020.04.017
  15. Migueles JH, Cadenas-Sanchez C, et al. Step-Based Metrics and Overall Physical Activity in Children With Overweight or Obesity: Cross-Sectional Study. JMIR mHealth uHealth 2020. doi: 10.2196/14841
  16. Landon-Cardinal O, Bachasson D, et al. Relationship between change in physical activity and in clinical status in patients with idiopathic inflammatory myopathy: a prospective cohort study. Seminars in Arthritis and Rheumatism 2020. doi: 10.1016/j.semarthrit.2020.06.014
  17. Mickute M, et al. Device‐measured physical activity and its association with physical function in adults with type 2 diabetes mellitus. Diabetic Medicine 2020. doi: 10.1111/dme.14393
  18. Dawkins NP, et al. Comparing 24 h physical activity profiles: Office workers, women with a history of gestational diabetes and people with chronic disease condition(s) Journal of Sports Sciences 2020, doi: 10.1080/02640414.2020.1812202
  19. Gaba A, et al. How do short sleepers use extra waking hours? A compositional analysis of 24-h time-use patterns among children and adolescents. International Journal of Behavioral Nutrition and Physical Activity 2020, doi: 10.1186/s12966-020-01004-8
  20. Migueles JH, et al. Associations of sleep with gray matter volume and their implications for academic achievement, executive function and intelligence in children with overweight/obesity. Ped Obesity 2020. doi: 10.1111/ijpo.12707
  21. Jakubec L et al. Is adherence to the 24-hour movement guidelines associated with a reduced risk of adiposity among children and adolescents? BMC Public Health 2020. doi: 10.1186/s12889-020-09213-3
  22. Henson et al. Physical behaviors and chronotype in people with type 2 diabetes. BMJ Open Diabetes Research & Care 2020. doi: 10.1136/bmjdrc-2020-001375
  23. Taylor et al. Effect of High‐Intensity Interval Training on Visceral and Liver Fat in Cardiac Rehabilitation: A Randomized Controlled Trial. Obesity 2020. doi: 10.1002/oby.22833
  24. Rowlands AV, et al. Physical activity for bone health: How much and/or how hard? MSSE 2020. doi: 10.1249/MSS.0000000000002380
  25. Halonen J, et al. Cross-sectional associations of neighbourhood socioeconomic disadvantage and greenness with accelerometer-measured leisure-time physical activity in a cohort of ageing workers. BMJ Open 2020. doi: 10.1136/bmjopen-2020-038673
  26. Stone JE, et al. Accuracy of the GENEActiv Device for Measuring Light Exposure in Sleep and Circadian Research. Clocks & Sleep 2020. doi: 10.3390/clockssleep2020012
  27. Crotti et al. Development of raw acceleration cut-points for wrist and hip accelerometers to assess sedentary behaviour and physical activity in 5–7-year-old children. Journal of Sports Science 2020. doi: 10.1080/02640414.2020.1740469
  28. Hurter et al. A Novel Mixed Methods Approach to Assess Children’s Sedentary Behaviors. JMPB 2020. doi: 10.1123/jmpb.2019-0040
  29. McGowan et al. Actigraphic patterns, impulsivity and mood instability in bipolar disorder, borderline personality disorder and healthy controls. Acta Psychiatrica Scan 2020. doi: 10.1111/acps.13148
  30. Bortone et al. Activity Energy Expenditure Predicts Clinical Average Levels of Physical Activity in Older Population: Results from Salus in Apulia Study. Sensors. 2020. doi: 10.3390/s20164585
  31. Rowlands AV et al. Enhancing the value of accelerometer-assessed physical activity: meaningful visual comparisons of data-driven translational accelerometer metrics. Sports Medicine 2020. doi: 10.1186/s40798-019-0225-9
  32. Harper, L., Hewitt, C.A., Litchfield, I., Morgan, M.D., Chanouzas, D., Caulfield, H.K., Coughlan, L., Dean, C., Fletcher, K., Cramp, F. and Greenfield, S., 2020. Management of fatigue with physical activity and behavioural change support in vasculitis: a feasibility study. Rheumatology.
  33. Wilkinson, T.J., Palmer, J., Gore, E.F. and Smith, A.C., 2020. The validity of the ‘General Practice Physical Activity Questionnaire’against accelerometery in patients with chronic kidney disease. Physiotherapy Theory and Practice, pp.1-10.
  34. Kuzik, N.O.C., 2020. Examining Movement Behaviours in Preschool-Aged Children: Novel Measurement and Data Analysis Techniques.
  35. Rastogi, T., Backes, A., Schmitz, S., Fagherazzi, G., van Hees, V. and Malisoux, L., 2020. Advanced analytical methods to assess physical activity behaviour using accelerometer raw time series data: a protocol for a scoping review. Systematic reviews, 9(1), pp.1-8.
  36. LaMunion, S.R., Crouter, S.E., Broskey, N.T., Altazan, A.D. and Redman, L.M., 2020. Discrimination of wear and non-wear in infants using data from hip-and ankle-worn devices. Plos one, 15(11), p.e0240604.
  37. Donnelly, S., Buchan, D.S., McLellan, G. and Arthur, R., 2020. Relationship between parent and child physical activity using novel acceleration metrics. Research Quarterly for Exercise and Sport, pp.1-9.
  38. Fairclough, S.J., Tyler, R., Dainty, J.R., Dumuid, D., Richardson, C., Shepstone, L. and Atkin, A.J., 2021. Cross-sectional associations between 24-hour activity behaviours and mental health indicators in children and adolescents: A compositional data analysis. Journal of Sports Sciences, pp.1-13.
  39. Ahmadi, M.N., Nathan, N., Sutherland, R., Wolfenden, L. and Trost, S.G., 2020. Non-wear or sleep? Evaluation of five non-wear detection algorithms for raw accelerometer data. Journal of sports sciences, 38(4), pp.399-404.
  40. Xu, Xin Yi. "Behavioral activation for improving sleep quality in family caregivers of people with dementia: a pilot randomized controlled trial." Doctoral Thesis. Hong Kong Polytechnic University (2020).
  41. Park, S., Park, K., Shim, J.S., Youm, Y., Kim, J., Lee, E. and Kim, H.C., 2020. Psychosocial factors affecting sleep misperception in middle-aged community-dwelling adults. PloS one, 15(10), p.e0241237.
  42. Jespersen, K.V., Madsen, J. and Vuust, P., 2020. Bedtime Music for Sleep Problems in older Adults with Dementia: a feasibility Study. Music and Medicine, 12(4), pp.222-230.
  43. da Costa, B.G., Chaput, J.P., Lopes, M.V., Malheiros, L.E., Tremblay, M.S. and Silva, K.S., 2020. Prevalence and sociodemographic factors associated with meeting the 24-hour movement guidelines in a sample of Brazilian adolescents. PloS one, 15(9), p.e0239833.
  44. Koopman-Verhoeff, M.E., van den Dries, M.A., Van Seters, J.J., Luijk, M.P.C.M., Tiemeier, H. and Luik, A.I., 2020. Melatoninegebruik en slaapproblemen bij schoolgaande Nederlandse kinderen. JGZ Tijdschrift voor jeugdgezondheidszorg, 52(5), pp.132-136.
  45. Bertrand, L., Bourguignon, C., Beaulieu, S., Storch, K.F. and Linnaranta, O., 2020. Suicidal Ideation and Insomnia in Bipolar Disorders: Idéation suicidaire et insomnie dans les troubles bipolaires. The Canadian Journal of Psychiatry, 65(11), pp.802-810.
  46. Steele, H., Gomez‐Duran, A., Pyle, A., Hopton, S., Newman, J., Stefanetti, R.J., Charman, S.J., Parikh, J.D., He, L., Viscomi, C. and Jakovljevic, D.G., 2020. Metabolic effects of bezafibrate in mitochondrial disease. EMBO molecular medicine, 12(3), p.e11589.
  47. Gershuny, J., Harms, T., Doherty, A., Thomas, E., Milton, K., Kelly, P. and Foster, C., 2020. Testing self-report time-use diaries against objective instruments in real time. Sociological Methodology, 50(1), pp.318-349.
  48. Cabanas‐Sánchez, V., Esteban‐Cornejo, I., Migueles, J.H., Banegas, J.R., Graciani, A., Rodríguez‐Artalejo, F. and Martínez‐Gómez, D., 2020. Twenty four‐hour activity cycle in older adults using wrist‐worn accelerometers: The seniors‐ENRICA‐2 study. Scandinavian journal of medicine & science in sports, 30(4), pp.700-708.
  49. Burchartz, A., Anedda, B., Auerswald, T., Giurgiu, M., Hill, H., Ketelhut, S.I., Kolb, S., Mall, C., Manz, K., Nigg, C.R. and Reichert, M., 2020. Assessing physical behavior through accelerometry–state of the science, best practices and future directions. Psychology of sport and exercise, 49.
  50. Zitser, J., Anatürk, M., Zsoldos, E., Mahmood, A., Filippini, N., Suri, S., Leng, Y., Yaffe, K., Singh-Manoux, A., Kivimaki, M. and Ebmeier, K., 2020. Sleep duration over 28 years, cognition, gray matter volume, and white matter microstructure: a prospective cohort study. Sleep, 43(5), p.zsz290.
  51. Scarlett, S., Nolan, H., Kenny, R.A. and O'Connell, M.D., 2020. Objective sleep duration in older adults: results from the Irish longitudinal study on ageing. Journal of the American Geriatrics Society, 68(1), pp.120-128.
  52. Jurado‐Fasoli, L., De‐la‐O, A., Molina‐Hidalgo, C., Migueles, J.H., Castillo, M.J. and Amaro‐Gahete, F.J., 2020. Exercise training improves sleep quality: A randomized controlled trial. European journal of clinical investigation, 50(3), p.e13202.
  53. Linnaranta, O., Bourguignon, C., Crescenzi, O., Sibthorpe, D., Buyukkurt, A., Steiger, H. and Storch, K.F., 2020. Late and instable sleep phasing is associated with irregular eating patterns in eating disorders. Annals of Behavioral Medicine, 54(9), pp.680-690.
  54. Tsanas, A., Woodward, E. and Ehlers, A., 2020. Objective characterization of activity, sleep, and circadian rhythm patterns using a wrist-worn actigraphy sensor: insights into posttraumatic stress disorder. JMIR mHealth and uHealth, 8(4), p.e14306.
  55. Lund, H.N., Pedersen, I.N., Johnsen, S.P., Heymann-Szlachcinska, A.M., Tuszewska, M., Bizik, G., Larsen, J.I., Kulhay, E., Larsen, A., Grønbech, B. and Østermark, H., 2020. Music to improve sleep quality in adults with depression-related insomnia (MUSTAFI): study protocol for a randomized controlled trial. Trials, 21(1), pp.1-10.
  56. Teräs, T., Rovio, S., Spira, A.P., Myllyntausta, S., Pulakka, A., Vahtera, J. and Stenholm, S., 2020. Associations of accelerometer-based sleep duration and self-reported sleep difficulties with cognitive function in late mid-life: the Finnish Retirement and Aging Study. Sleep medicine, 68, pp.42-49.
  57. Duncan, M.J., Fenton, S., Brown, W.J., Collins, C.E., Glozier, N., Kolt, G.S., Holliday, E.G., Morgan, P.J., Murawski, B., Plotnikoff, R.C. and Rayward, A.T., 2020. Efficacy of a multi-component m-health weight-loss intervention in overweight and obese adults: a randomised controlled trial. International journal of environmental research and public health, 17(17), p.6200.
  58. Rubín, L., Gába, A., Dygrýn, J., Jakubec, L., Materová, E. and Vencálek, O., 2020. Prevalence and correlates of adherence to the combined movement guidelines among Czech children and adolescents. BMC public health, 20(1), pp.1-11.
  59. Torres-Lopez, L.V., Cadenas-Sanchez, C., Migueles, J.H., Adelantado-Renau, M., Plaza-Florido, A., Solis-Urra, P., Molina-Garcia, P. and Ortega, F.B., 2020. Associations of sedentary behaviour, physical activity, cardiorespiratory fitness and body composition with risk of sleep-related breathing disorders in children with overweight/obesity: A cross-sectional study. Journal of Clinical Medicine, 9(5), p.1544.
  60. Wendt, A., da Silva, I.C.M., Gonçalves, H., Menezes, A., Barros, F. and Wehrmeister, F.C., 2020. Short-term effect of physical activity on sleep health: A population-based study using accelerometry. Journal of Sport and Health Science.
  61. Iakovakis, D., Mastoras, R.E., Hadjidimitriou, S., Charisis, V., Bostanjopoulou, S., Katsarou, Z., Klingelhoefer, L., Reichmann, H., Trivedi, D., Chaudhuri, R.K. and Hadjileontiadis, L.J., 2020, July. Smartwatch-based activity analysis during sleep for early Parkinson’s disease detection. In 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 4326-4329). IEEE.
  62. Lavin‐Gonzalez, P., Bourguignon, C., Crescenzi, O., Beaulieu, S., Storch, K.F. and Linnaranta, O., 2020. Inactograms and objective sleep measures as means to capture subjective sleep problems in patients with a bipolar disorder. Bipolar disorders, 22(7), pp.722-730.
  63. Jurado-Fasoli, L., Mochon-Benguigui, S., Castillo, M.J. and Amaro-Gahete, F.J., 2020. Association between sleep quality and time with energy metabolism in sedentary adults. Scientific reports, 10(1), pp.1-10.
  64. Carter, S., Hill, A.M., Yandell, C., Buckley, J.D., Tan, S.Y., Rogers, G.B., Childs, J., Matheson, M., Lamb, K., Ward, S. and Stanton, T.R., 2020. Study protocol for a 9-month randomised controlled trial assessing the effects of almonds versus carbohydrate-rich snack foods on weight loss and weight maintenance. BMJ open, 10(7), p.e036542.
  65. Chun, H.Y.Y., Carson, A.J., Tsanas, A., Dennis, M.S., Mead, G.E., Calabria, C. and Whiteley, W.N., 2020. Telemedicine cognitive behavioral therapy for anxiety after stroke: proof-of-concept randomized controlled trial. Stroke, 51(8), pp.2297-2306.
  66. Suorsa, K., Pulakka, A., Leskinen, T., Pentti, J., Holtermann, A., Heinonen, O.J., Sunikka, J., Vahtera, J. and Stenholm, S., 2020. Comparison of sedentary time between thigh-worn and wrist-worn accelerometers. Journal for the Measurement of Physical Behaviour, 3(3), pp.234-243.
  67. Carneiro-Barrera, A., Amaro-Gahete, F.J., Acosta, F.M. and Ruiz, J.R., 2020. Body composition impact on sleep in young adults: The mediating role of sedentariness, physical activity, and diet. Journal of clinical medicine, 9(5), p.1560.
  68. Plekhanova, T., Rowlands, A.V., Yates, T., Hall, A., Brady, E.M., Davies, M., Khunti, K. and Edwardson, C.L., 2020. Equivalency of sleep estimates: comparison of three research-grade accelerometers. Journal for the Measurement of Physical Behaviour, 1(aop), pp.1-10.
  69. Wang, Y.J., Duan, W. and Lei, X., 2020. Impaired Coupling of the Brain’s Default Network During Sleep Deprivation: A Resting-State EEG Study. Nature and Science of Sleep, 12, p.937.
  70. Verhoog, S., Braun, K.V., Bano, A., van Rooij, F.J., Franco, O.H., Koolhaas, C.M. and Voortman, T., 2020. Associations of activity and sleep with quality of life: a compositional data analysis. American journal of preventive medicine, 59(3), pp.412-419.
  71. Martinez-Avila, W.D., Sanchez-Delgado, G., Acosta, F.M., Jurado-Fasoli, L., Oustric, P., Labayen, I., Blundell, J.E. and Ruiz, J.R., 2020. Eating Behavior, Physical Activity and Exercise Training: A Randomized Controlled Trial in Young Healthy Adults. Nutrients, 12(12), p.3685.
  72. Li, X. and Zhao, H., 2020. Automated feature extraction from population wearable device data identified novel loci associated with sleep and circadian rhythms. PLoS genetics, 16(10), p.e1009089.
  73. da Costa, B.G., Chaput, J.P., Lopes, M.V., Malheiros, L.E., Tremblay, M.S. and Silva, K.S., 2020. Prevalence and sociodemographic factors associated with meeting the 24-hour movement guidelines in a sample of Brazilian adolescents. PloS one, 15(9), p.e0239833.
  74. Rowlands, A.V., 2020. Measuring physical activity with body-worn accelerometers. In The Routledge Handbook of Youth Physical Activity (pp. 330-346). Routledge.
  75. Taylor, A.H., Taylor, R.S., Ingram, W.M., Anokye, N., Dean, S., Jolly, K., Mutrie, N., Lambert, J., Yardley, L., Greaves, C. and King, J., 2020. Adding web-based behavioural support to exercise referral schemes for inactive adults with chronic health conditions: the e-coachER RCT. Health Technology Assessment (Winchester, England), 24(63), p.1.
  76. Koopman-Verhoeff, M.E., van den Dries, M.A., van Seters, J.J., Luijk, M.P., Tiemeier, H. and Luik, A.I., 2020. Sleep problems and melatonin use in school-aged children. Bedtime studies, 173(9), p.129.
  77. Maguire, D.G., Ruddock, M.W., Milanak, M.E., Moore, T., Cobice, D. and Armour, C., 2020. Sleep, a governor of morbidity in PTSD: A systematic review of biological markers in PTSD-related sleep disturbances. Nature and Science of Sleep, 12, p.545.
  78. Sharp, K.J., South, C.C., Fatt, C.C., Trivedi, M.H. and Rethorst, C.D., 2020. Pilot Studies to Evaluate Feasibility of a Physical Activity Intervention for Persons With Depression. Journal of Sport and Exercise Psychology, 1(aop), pp.1-9.
  79. Mochón-Benguigui, S., Carneiro-Barrera, A., Castillo, M.J. and Amaro-Gahete, F.J., 2020. Is Sleep Associated with the S-Klotho Anti-Aging Protein in Sedentary Middle-Aged Adults? The FIT-AGEING Study. Antioxidants, 9(8), p.738.
  80. Capstick, H.T. and Guxens, M., Study II: Estimated all-day and evening whole-brain radiofrequency electromagnetic fields doses and sleep in preadolescents. Radiofrequency electromagnetic fields exposure, sleep, and neurodevelopment in preadolescents and adolescents, p.75.
  81. Feng, H., 2020. Mental Disorders and Sleep and Circadian Rhythm Dysregulation in the Offspring of Parents with Bipolar Disorder (Doctoral dissertation, Hong Kong University of Science and Technology (Hong Kong)).
  82. Antonakos, C., Baiers, R., Dubowitz, T., Clarke, P. and Colabianchi, N., 2020. Associations between body mass index, physical activity and the built environment in disadvantaged, minority neighborhoods: Predictive validity of GigaPan® imagery. Journal of transport & health, 17, p.100867.

2019

  1. Euler R, Yakes Jimenez E, et al. Rural–Urban Differences in Baseline Dietary Intake and Physical Activity Levels of Adolescents. Preventing Chronic Disease, 2019. doi: 10.5888/pcd16.180200
  2. Bradley AJ, Anderson KN, et al. The association between sleep and cognitive abnormalities in bipolar disorder. Psychological Medicine, 2019. doi: 10.1017/S0033291718004038
  3. Jones SE, Lane JM, et al. Genome-wide association analyses of chronotype in 697,828 individuals provides insights into circadian rhythms. Nature Communications, 2019. doi: 10.1038/s41467-018-08259-7
  4. Exel J, Mateus N, et al. Physical activity and sedentary behavior in amateur sports: master athletes are not free from prolonged sedentary time. Sport Sciences for Health, 2019. doi: 10.1007/s11332-019-00527-3
  5. Bielemann RM, Ramires VV, et al. Is vigorous-intensity physical activity required for improving bone mass in adolescence? Findings from a Brazilian birth cohort. Osteoporosis International, 2019. doi: 10.1007/s00198-019-04862-6
  6. Lane JM, Jones SE, et al. Biological and clinical insights from genetics of insomnia symptoms. Nature Genetics, doi: 10.1038/s41588-019-0361-7
  7. McLellan G, Arthur R, et al. Segmented sedentary time and physical activity patterns throughout the week from wrist-worn ActiGraph GT3X+ accelerometers among children 7-12 years old. Journal of Sport and Health Science, 2019. doi: 10.1016/j.jshs.2019.02.005
  8. Boddy LM, Noonan RJ, et al. The comparability of sedentary time estimates derived from wrist worn GENEActiv accelerometers and waist worn ActiGraph accelerometers in children. JSAMS, 2019. doi: 10.1016/j.jsams.2018.03.015
  9. Zalewski BM, Szajewska H. No Effect of Glucomannan on Body Weight Reduction in Children and Adolescents with Overweight and Obesity: A Randomized Controlled Trial. The Journal of Pediatrics, 2019. doi: 10.1016/j.jpeds.2019.03.044
  10. Mavilidi MF, Lubans R, et al. Integrating physical activity into the primary school curriculum: rationale and study protocol for the “Thinking while Moving in English” cluster randomized controlled trial. BMC Public Health, 2019. doi: 10.1186/s12889-019-6635-2.
  11. da Silva BGC, da Silva IC, et al. Associations of physical activity and sedentary time with body composition in Brazilian young adults. Scientific Reports, 2019. doi: 10.1038/s41598-019-41935-2.
  12. Boddy LM, Noonan RJ, et al. The backwards comparability of wrist worn GENEActiv and waist worn ActiGraph accelerometer estimates of sedentary time in children. JSAMS, 2019. doi: 10.1016/j.jsams.2019.02.001.
  13. Farina N, Sherlock G et al. Acceptability and feasibility of wearing activity monitors in community‐dwelling older adults with dementia. Geriatric Psychiatry 2019. doi: 10.1002/gps.5064
  14. Thewlis D, Bahl JS, et al. Objectively measured 24-hour activity profiles before and after total hip arthroplasty. The Bone & Joint Journal. 2019. doi: 10.1302/0301-620X.101B4.BJJ-2018-1240.R1
  15. Amaro-Gahete FJ, De-la-O Alejandro, et al. Effects of different exercise training programs on body composition: A randomized control trial. Scan J of Med & Science in Sports. 2019. doi: 10.1111/sms.13414
  16. Hausler N, Marques-Vidal P et al. Association between actigraphy-based sleep duration variability and cardiovascular risk factors – Results of a population-based study. Sleep Medicine. 2019. doi: 10.1016/j.sleep.2019.02.008.
  17. Gomez-Bruton A, Arenaza L, et al. Associations of dietary energy density with body composition and cardiometabolic risk in children with overweight and obesity: role of energy density calculations, under-reporting energy intake and physical activity. British Journal of Nutrition. 2019. doi: 10.1017/S0007114519000278.
  18. Amaro-Gahete FJ, De-la-O Alejandro, et al. Association of physical activity and fitness with S-Klotho plasma levels in middle-aged sedentary adults: The FIT-AGEING study. Maturitas. 2019. doi: 10.1016/j.maturitas.2019.02.001.
  19. Koopman‐Verhoeff ME, Serdarevic F. et al. Preschool family irregularity and the development of sleep problems in childhood: a longitudinal study. The Journal of Child Psychology and Psychiatry. 2019. doi: 10.1111/jcpp.13060
  20. Plaza-Florido A,Migueles JH, et al. Heart Rate Is a Better Predictor of Cardiorespiratory Fitness Than Heart Rate Variability in Overweight/Obese Children: The ActiveBrains Project. Front Physiol. 2019. doi: 10.3389/fphys.2019.00510
  21. da Silva SG, Evenson KR, et al. How many days are needed to estimate wrist-worn accelerometry-assessed physical activity during the second trimester in pregnancy? PLoS ONE. 2019. doi: doi.org/10.1371/journal.pone.0211442
  22. Rowlands AV, Sherar LB, et al. A data-driven, meaningful, easy to interpret, standardised accelerometer outcome variable for global surveillance. Journal of Science and Med. in Sport 2019. doi: 10.1016/j.jsams.2019.06.016
  23. Papandreou C, Bullo M, et al. High sleep variability predicts a blunted weight loss response and short sleep duration a reduced decrease in waist circumference in the PREDIMED-Plus Trial. Int J of Obesity. 2019. doi: 10.1038/s41366-019-0401-5
  24. Richmond RC, Anderson EL, et al. Investigating causal relations between sleep traits and risk of breast cancer in women: mendelian randomisation study. BMJ 2019. doi: 10.1136/bmj.l2327
  25. Rowlands AV, Plekhanova T, et al. Providing a Basis for Harmonization of Accelerometer-Assessed Physical Activity Outcomes Across Epidemiological Datasets. J for the Measurement of Phys Behavior 2019. doi: 10.1123/jmpb.2018-0073
  26. Acosta FM, Sanchez-Delgao G, et al. Sleep duration and quality are not associated with brown adipose tissue volume or activity - as determined by 18F-FDG uptake, in young, sedentary adults. Sleep 2019. doi: 10.1093/sleep/zsz177
  27. Chen B, Bernard JY, et al. Socio-demographic and maternal predictors of adherence to 24-hour movement guidelines in Singaporean children. International Journal of Behavioral Nutrition and Physical Activity. 2019. doi: 10.1186/s12966-019-0834-1
  28. Sanders SG, Jimenez EY. et al. Estimated Physical Activity in Adolescents by Wrist-Worn GENEActiv Accelerometers. Journal of Physical Activity and Health. 2019. doi: 10.1123/jpah.2018-0344
  29. Benadjaoud MA, Menai M, et atl. The association between accelerometer-assessed physical activity and respiratory function in older adults differs between smokers and non-smokers. Nature Scientific Reports, 2019. doi: 10.1038/s41598-019-46771-y
  30. Panandreou C, Diaz-Lopez A, et al. Long Daytime Napping Is Associated with Increased Adiposity and Type 2 Diabetes in an Elderly Population with Metabolic Syndrome. Journal of Clinical Medicine. 2019. doi: 10.3390/jcm8071053
  31. Difrancesco S, Lamers F, et al. Sleep, circadian rhythm, and physical activity patterns in depressive and anxiety disorders: A 2‐week ambulatory assessment study. Depression & Anxiety, 2019. doi: 10.1002/da.22949
  32. Wang H, Lane JM, et al. Genome-wide association analysis of self-reported daytime sleepiness identifies 42 loci that suggest biological subtypes, Nature Communications 2019. doi: 10.1038/s41467-019-11456-7
  33. Hausler N, Marques-Vidal P, et al. Does sleep predict next-day napping or does napping influence same-day nocturnal sleep? Results of a population-based ecological momentary assessment study. Sleep Medicine, 2019. doi: 10.1016/j.sleep.2019.04.014
  34. Bielemann RM, LaCroix AZ, et al. Objectively Measured Physical Activity Reduces the Risk of Mortality among Brazilian Older Adults. J of the American Geriatrics Society 2019. doi: 10.1111/jgs.16180
  35. Wu J, Einerson B, et al. Association between sleep quality and physical activity in postpartum women. Sleep Health. 2019. doi: 10.1016/j.sleh.2019.07.008
  36. McLellen G, Arthur R, et al. Segmented sedentary time and physical activity patterns throughout the week from wrist-worn ActiGraph GT3X+ accelerometers among children 7–12 years old. J of Sport and Health Science 2019. doi: 10.1016/j.jshs.2019.02.005
  37. Khan M, Bell R, et al. Effects of a School Based Intervention on Children’s Physical Activity and Healthy Eating: A Mixed-Methods Study. Int J Environ Res 2019. doi: 10.3390/ijerph16224320
  38. Buchan D S, McLellan G, et al. The use of the intensity gradient and average acceleration metrics to explore associations with BMI z-score in children. J of Sports Sciences 2019. doi: 10.1080/02640414.2019.1664536
  39. Watson A, Maher C, et al. Life on holidays: study protocol for a 3-year longitudinal study tracking changes in children’s fitness and fatness during the in-school versus summer holiday period. BMC Public Health 2019. doi: 10.1186/s12889-019-7671-7
  40. Teras T, Rovio S, et al. Associations of accelerometer-based sleep duration and self-reported sleep difficulties with cognitive function in late mid-life: The Finnish Retirement and Aging Study. Sleep Medicine 2019, doi:10.1016/j.sleep.2019.08.024
  41. Vasankari V, Halonen J, et al. Personalised eHealth intervention to increase physical activity and reduce sedentary behaviour in rehabilitation after cardiac operations: study protocol for the PACO randomised controlled trial (NCT03470246). BMJ Open Sport & Exercise Medicine 2019. doi: 10.1136/bmjsem-2019-000539
  42. Mora-Gonzalez G, Migueles J, et al. Sedentarism, Physical Activity, Steps, and Neurotrophic Factors in Obese Children. Med Sci in Sports and Exercise 2019. doi: 10.1249/MSS.0000000000002064
  43. Diniz-Sousa F, Veras L, et al. Accelerometry calibration in people with class II-III obesity: Energy expenditure prediction and physical activity intensity identification. Gait & Posture 2019. doi: 10.1016/j.gaitpost.2019.11.008
  44. Duncan MJ, Rowlands A, et al. Using accelerometry to classify physical activity intensity in older adults: What is the optimal wear-site? European J of Sport Science 2019. doi: 10.1080/17461391.2019.1694078
  45. Owen, M, Kerner, C et al. The Feasibility of a Novel School Peer-Led Mentoring Model to Improve the Physical Activity Levels and Sedentary Time of Adolescent Girls: The Girls Peer Activity (G-PACT) Project. Children 2019. doi: 10.3390/children5060067
  46. Migueles JH, Cadenas-Sanchez C, et al. Comparability of accelerometer signal aggregation metrics across placements and dominant wrist cut points for the assessment of physical activity in adults. Scientific Reports 2019. doi: 10.1038/s41598-019-54267-y
  47. Tillin T, Tuson C. et al. Yoga and Cardiovascular Health Trial (YACHT): a UK-based randomised mechanistic study of a yoga intervention plus usual care versus usual care alone following an acute coronary event. BMJ Open 2019. doi: 10.1136/bmjopen-2019-030119
  48. Grimes L, Outtrim JG, et al. Accelerometery as a measure of modifiable physical activity in high-risk elderly preoperative patients: a prospective observational pilot study. BMJ Open 2019. doi: 10.1136/bmjopen-2019-032346
  49. Dicks ND, Kotarsky CJ. et al. Contribution of Protein Intake and Concurrent Exercise to Skeletal Muscle Quality with Aging. The Journal of Frailty & Aging. 2019. doi: 10.14283/jfa.2019.40
  50. Wendt A, da Silva ICM, et al. Sleep parameters measured by accelerometry: descriptive analyses from the 22-year follow-up of the Pelotas 1993 Birth Cohort. Sleep Medicine 2019. doi: 10.1016/j.sleep.2019.10.020
  51. Teras T, Rovio S, et al. Associations of accelerometer-based sleep duration and self-reported sleep difficulties with cognitive function in late mid-life: The Finnish Retirement and Aging Study. Sleep Medicine 2019. doi: 10.1016/j.sleep.2019.08.024
  52. Jones S, van Hees VT, et al. Genetic studies of accelerometer-based sleep measures yield new insights into human sleep behaviour. Nature Communications. 2019, doi: 10.1038/s41467-019-09576-1.
  53. Zhu G, Catt M, et al. Objective sleep assessment in >80,000 UK mid-life adults: Associations with sociodemographic characteristics, physical activity and caffeine. PLoS ONE. 2019. doi: 0.1371/journal.pone.0226220
  54. Galmes-Panades AM, Varela-Mato V, 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. IJBNPA 2019. doi: 10.1186/s12966-019-0892-4
  55. Alley S, van Uffelen JGZ, et al. Efficacy of a computer-tailored web-based physical activity intervention using Fitbits for older adults: a randomised controlled trial protocol. BMJ Open. 2019. doi: 10.1136/bmjopen-2019-033305
  56. Ricardo LIC, da Silva IC, et al. Objectively measured physical activity in one-year-old children from a Brazilian cohort: levels, patterns and determinants. IJBNPA 2019. doi: 10.1186/s12966-019-0895-1

2018

  1. van de Langenberg D, Vlaanderen JJ, et al. Diet, Physical Activity, and Daylight Exposure Patterns in Night-Shift Workers and Day Workers. Annals of Work Exposures and Health, 2018. doi: 10.1093/annweh/wxy097
  2. Chandler J, Beets M et al. Wrist-Based Accelerometer Cut-Points to Identify Sedentary Time in 5–11-Year-Old Children. Children, 2018. doi: 10.3390/children5100137
  3. Bittner A K, Haythornthwaite, JA, et al. Subjective and Objective Measures of Daytime Activity and Sleep Disturbance in Retinitis Pigmentosa. Optometry and Vision Science, 2018. doi: 10.1097/OPX.0000000000001265
  4. Migueles JH, Cadenas‐Sanchez C, et al. Comparability of published cut‐points for the assessment of physical activity: Implications for data harmonization. Scan J of Med & Sci in Sports, 2018. doi: 10.1111/sms.13356
  5. Sanders GJ, Boddy LM, et al. Evaluation of wrist and hip sedentary behaviour and moderate-to-vigorous physical activity raw acceleration cutpoints in older adults. Journal of Sports Sciences, 2018. doi: 10.1080/02640414.2018.1555904
  6. Taylor SL, Noonan RJ, et al. Acceptability and Feasibility of Single-Component Primary School Physical Activity Interventions to Inform the AS:Sk Project. Children, 2018. doi: 10.3390/children5120171
  7. Sayre MK, Pike IL, et al. High levels of objectively measured physical activity across adolescence and adulthood among the Pokot pastoralists of Kenya. American Journal of Human Biology, 2018. doi: 10.1002/ajhb.23205.
  8. Chevance G, Berry Tanya, et al. Changing implicit attitudes for physical activity with associative learning. German Journal of Exercise and Sport Research, 2018. doi: 10.1007/s12662-018-0559-3
  9. Sukumar N, Dallosso H, et al. Baby Steps – a structured group education programme with accompanying mobile web application designed to promote physical activity in women with a history of gestational diabetes: study protocol for a randomised controlled trial. BMC Trials, 2018. doi:10.1186/s13063-018-3067-8
  10. Dallosso H, Tom Yates T, et al. Movement through Active Personalised engagement (MAP) — a self-management programme designed to promote physical activity in people with multimorbidity: study protocol for a randomised controlled trial. BMC Trials, 2018. doi: 10.1186/s13063-018-2939-2
  11. Rosique-Esteban N, Papandreou C, et al. Cross-sectional associations of objectively-measured sleep characteristics with obesity and type 2 diabetes in the PREDIMED-Plus trial. Sleep, 2018. doi: 10.1093/sleep/zsy190
  12. Konstabel K, Chopra S. et al. Accelerometry-Based Physical Activity Assessment for Children and Adolescents. Springer, Cham, 2018. doi: 10.1007/978-3-319-98857-3_7
  13. Buchan DS, McLellan G, et al. Comparing physical activity estimates in children from hip-worn Actigraph GT3X+ accelerometers using raw and counts based processing methods. Journal of Sports Sciences, 2018. doi: 10.1080/02640414.2018.1527198.
  14. Herring LY, Dallosso H, et al. Physical Activity after Cardiac EventS (PACES) – a group education programme with subsequent text-message support designed to increase physical activity in individuals with diagnosed coronary heart disease: study protocol for a randomised controlled trial. 2018, doi: 10.1186/s13063-018-2923-x
  15. Edwardson CL, Yates T. Effectiveness of the Stand More AT (SMArT) Work intervention: cluster randomised controlled trial. BMJ, 2018. doi: 10.1136/bmj.k3870
  16. Duncan MJ, Brown WJ, et al. Examining the efficacy of a multicomponent m-Health physical activity, diet and sleep intervention for weight loss in overweight and obese adults: randomised controlled trial protocol. BMJ Open, 2018. doi: 10.1136/bmjopen-2018-026179.
  17. Shelley J, Fairclough SJ, et al. A formative study exploring perceptions of physical activity and physical activity monitoring among children and young people with cystic fibrosis and health care professionals. BMC Pediatrics, 2018. doi: 10.1186/s12887-018-1301-x
  18. Chapman JJ, Suetani S, et al. Protocol for a randomised controlled trial of interventions to promote adoption and maintenance of physical activity in adults with mental illness. BMJ Open, 2018. doi: 10.1136/bmjopen-2018-023460
  19. Pérez-López J, Benavente-Marín JC, et al. Duración de sueño en personas mayores con síndrome metabólico. RICCAFD _doi: 10.24310/riccafd.2018.v7i2.5096
  20. Horne S, Hay K, An evaluation of sleep disturbance on in-patient psychiatric units in the UK. BJPsych Bulletin 2018, doi: 10.1192/bjb.2018.42
  21. Shepherd AI, Pulsford R, et al. Physical activity, sleep, and fatigue in community dwelling Stroke Survivors. Scientific Reports 2018, doi: 10.1038/s41598-018-26279-7
  22. Miller A, Eather N, et al. Associations of object control motor skill proficiency, game play competence, physical activity and cardiorespiratory fitness among primary school children. Journal of Sports Sciences 2018, doi: 10.1080/02640414.2018.1488384
  23. Jimenez-Moreno AC, Charman SJ, et al. Analyzing walking speeds with ankle and wrist worn accelerometers in a cohort with myotonic dystrophy. Disbility and Rehabilitation 2018, doi: 10.1080/09638288.2018.1482376
  24. Buchan DS, McSeveney F, et al. A comparison of physical activity from Actigraph GT3X+ accelerometers worn on the dominant and non‐dominant wrist. Clinical Physiology and Functional Imaging 2018. doi: 10.1111/cpf.12538
  25. Acosta FM, Martinez-Tellez B, et al. Association of objectively measured physical activity with brown adipose tissue volume and activity in young adults. JCEM 2018, doi: 10.1210/jc.2018-01312
  26. Stiles V, Pearce M, et al. Wrist-worn Accelerometry for Runners: Objective Quantification of Training Load. MSSE 2018, doi: 10.1249/MSS.0000000000001704
  27. Lambert JD, Greaves CJ, et al. Web-Based Intervention Using Behavioral Activation and Physical Activity for Adults With Depression (The eMotion Study): Pilot Randomized Controlled Trial. Journal of medical Internet Research 2018, doi: 10.2196/10112
  28. Lean MEJ, Leslie WS et al. Primary care-led weight management for remission of type 2 diabetes (DiRECT): an open-label, cluster-randomised trial. Lancet 2018, doi: 10.1016/S0140-6736(17)33102-1
  29. Okkersen K, Jimenez-Moreno C et al. Cognitive behavioural therapy with optional graded exercise therapy in patients with severe fatigue with myotonic dystrophy type 1: a multicentre, single-blind, randomised trial, Lancet Neurology, 2018, doi: 10.1016/S1474-4422(18)30203-5.
  30. Cassidy S, Fuller H et al Accelerometer-derived physical activity in those with cardio-metabolic disease compared to healthy adults: a UK Biobank study of 52,556 participants, Acta Diabetologica, 2018, doi: 10.1007/s00592-018-1161-8
  31. Warehime S, Dinkel D et al. Postpartum physical activity and sleep levels in overweight, obese and normal-weight mothers, British Journal of Midwifery 2018, doi: 10.12968/bjom.2018.26.6.400
  32. Norris M, Shepherd A et al. Physical activity, sleep, and fatigue in community dwelling Stroke Survivors Scientific Reports 2018, DOI:10.1038/s41598-018-26279-7
  33. Müller-Riemenschneider F, Petrunoff N et al. Prescribing Physical Activity in Parks to Improve Health and Wellbeing: Protocol of the Park Prescription Randomized Controlled Trial. Int. J. Environ. Res. Public Health 2018, doi: 10.3390/ijerph15061154
  34. Bielemann RM, dos S Vaz J et al. Are consumption of dairy products and physical activity independently related to bone mineral density of 6-year-old children? Longitudinal and cross-sectional analyses in a birth cohort from Brazil, Public Health Nutrition 2018, doi: 10.1017/S1368980018001258
  35. Taylor SL, Noonan RJ, et al. Evaluation of a Pilot School-Based Physical Activity Clustered Randomised Controlled Trial—Active Schools: Skelmersdale, Int. J. Environ. Res. Public Health, 2018, doi: 10.3390/ijerph15051011
  36. Owen M, Kerner C et al. The Feasibility of a Novel School Peer-Led Mentoring Model to Improve the Physical Activity Levels and Sedentary Time of Adolescent Girls: The Girls Peer Activity (G-PACT) Project. MDPI, 2018, doi: 10.3390/children5060067
  37. Harrington DM, Davies MJ et al. Effectiveness of the ‘Girls Active’ school-based physical activity programme: A cluster randomised controlled trial. International Journal of Behavioral Nutrition and Physical Activity, 2018, doi: 10.1186/s12966-018-0664-6
  38. Innerd P, Harrison R et al. Using open source accelerometer analysis to assess physical activity and sedentary behaviour in overweight and obese adults. BMC Public Health, 2018, doi: 10.1186/s12889-018-5215-1
  39. Westbury LD, Dodds RM et al. Associations Between Objectively Measured Physical Activity, Body Composition and Sarcopenia: Findings from the Hertfordshire Sarcopenia Study (HSS), Calcified tissue international, 2018, doi:10.1007/s00223-018-0413-5)
  40. McLellan G, Arthur R et al. Wear compliance, sedentary behaviour and activity in free-living children from hip-and wrist-mounted ActiGraph GT3X+ accelerometers,Journal of Sport Science, 2018, doi:10.1080/02640414.2018.1461322
  41. Gubelmann C, Heinzer R et al. Physical Activity is Associated with Higher Sleep Efficiency in the General Population: The CoLaus Study. Sleep, 2018, doi: 10.1093/sleep/zsy070
  42. Phelan S, Wing RR, et al. Randomized controlled clinical trial of behavioral lifestyle intervention with partial meal replacement to reduce excessive gestational weight gain. The American Journal of Clinical Nutrition, 2018, doi: 10.1093/ajcn/nqx043
  43. da Silva SG, Evenson KR, et al. Correlates of accelerometer‐assessed physical activity in pregnancy:The 2015 Pelotas (Brazil) Birth Cohort Study. Scandinavian journal of medicine and science in sports, 2018. doi: 10.1111/sms.13083
  44. Lloyd J, CStat SC, et al. Effectiveness of the Healthy Lifestyles Programme (HeLP) to prevent obesity in UK primary-school children: a cluster randomised controlled trial. The Lancet Child & Adolescent Health, 2018. doi: doi: 10.1016/S2352-4642(17)30151-7
  45. Florez KR, Richardson AS, et al. The Power of Social Networks and Social Support in Promotion of Physical Activity and Body Mass Index among African American Adults. SSM - Population Health, 2018. doi: 10.1016/j.ssmph.2018.03.004
  46. Hurter L., Fairclough SJ, et al. Establishing Raw Acceleration Thresholds to Classify Sedentary and Stationary Behaviour in Children. children, 2018. doi: 10.3390/children5120172
  47. Kerr J, Marinac CR et al. Comparison of Accelerometry Methods for Estimating Physical Activity, Med Sci Sports Exerc. 2017. doi: 10.1249/MSS.0000000000001124
  48. Montoye AHK, Westgate BS, et al. Cross-validation and out-of-sample testing of physical activity intensity predictions with a wrist-worn. J Appl Phys, 2018. doi: 10.1152/japplphysiol.00760.2017
  49. Khanna A, Jopson L, et al. Rituximab for the treatment of fatigue in primary biliary cholangitis (formerly primary biliary cirrhosis): a randomised controlled trial. Efficacy Mech Eval 2018. doi: 10.3310/eme05020
  50. Lim SER, Dodds R, et al. Physical activity among hospitalised older people: insights from upper and lower limb accelerometry. Aging Clin Exp Res. 2018. doi: 10.1007/s40520-018-0930-0.

2017

  1. Kwasnicka D, Vandelanotte C, et al. Comparing motivational, self-regulatory and habitual processes in a computer-tailored physical activity intervention in hospital employees - protocol for the PATHS randomised controlled trial. BMC Public Health, 2017. doi: 10.1186/s12889-017-4415-4.
  2. Taylor J, Keating SE, et al. Study protocol for the FITR Heart Study: Feasibility, safety, adherence, and efficacy of high intensity interval training in a hospital-initiated rehabilitation program for coronary heart disease. Contemporary Clinical Trials Communications, 2017. DOI: 10.1016/j.conctc.2017.10.002
  3. da Silva ICM, Hino AA,et al. Built environment and physical activity: domain- and activity-specific associations among Brazilian adolescents. BMC Public Health, 2017. doi: 10.1186/s12889-017-4538-7.
  4. Noonan RJ, Boddy LM, et al. Comparison of children’s free-living physical activity derived from wrist and hip raw accelerations during the segmented week. J Sports Sci, 2017. doi: 10.1080/02640414.2016.1255347. Epub 2016 Nov 14.
  5. Lloyd J, Creanor S, et al. Effectiveness of the Healthy Lifestyles Programme (HeLP) to prevent obesity in UK primary-school children: a cluster randomised controlled trial. BMC Public Health, 2017. DOI: 10.1186/s12889-017-4196-9
  6. Kolle E, Horta BL, et al. Does objectively measured physical activity modify the association between early weight gain and fat mass in young adulthood? BMC Public Health, 2017. DOI: 10.1186/s12889-017-4924-1
  7. Chevance G., Caudroit J., Do implicit attitudes toward physical activity and sedentary behavior prospectively predict objective physical activity among persons with obesity? Journal of Behavioral Medicine, 2017. DOI: 10.1007/s10865-017-9881-8
  8. Stiles VH, Metcalf BS, et al. A small amount of precisely measured high-intensity habitual physical activity predicts bone health in pre- and post-menopausal women in UK Biobank. Int J Epidemiol 29 June 2017. doi: 10.1093/ije/dyx08
  9. Atkins C, Baxter M, et al. Measuring sedentary behaviors in patients with idiopathic pulmonary fibrosis using wrist-worn accelerometers. The Clinical Respiratory Journal 8 January 2017. DOI: 10.1111/crj.12589
  10. Koolhaas CM, van Rooij FJA, et al. Objective Measures of Activity in the Elderly: Distribution and Associations With Demographic and Health Factors. J Am Med Dir Assoc. 2017 June. doi: 10.1016/j.jamda.2017.04.017 (Note: authors confirmed that GGIR was used, but this was accidentally not reported in the manuscript)
  11. Kim Y, Hibbing P, et al. Surveillance of Youth Physical Activity and Sedentary Behavior With Wrist Accelerometry. American journal of preventive medicine 2017, 25(6): 872-79. doi: 10.1016/j.amepre.2017.01.012.
  12. Bachasson D, Landon-Cardinal O, et al. Physical Activity Monitoring: A Promising Outcome Measure in Idiopathic Inflammatory Myopathies. Neurology. 2017 May 31. pii: 10.1212/WNL.0000000000004061. doi: 10.1212/WNL.0000000000004061.
  13. Nakamura PM, Mielke GI, et al. Physical Activity Throughout Adolescence and Hba1c in Early Adulthood: Birth Cohort Study. J Phys Act Health. 2017 May;14(5):375-381. doi: 10.1123/jpah.2016-0245. Epub 2017 Feb 7.
  14. Taylor SL, Curry, et al. Predictors of Segmented School Day Physical Activity and Sedentary Time in Children from a Northwest England Low-Income Community. Int J Environ Res Public Health. 2017 May 16;14(5). pii: E534. doi: 10.3390/ijerph14050534.
  15. Richardson AS, Troxel WM, One size doesn’t fit all: cross-sectional associations between neighborhood walkability, crime and physical activity depends on age and sex of residents. BMC Public Health. 2017. 17:97. DOI: 10.1186/s12889-016-3959-z
  16. Lloyd J, Creanor S, et al. Trial baseline characteristics of a cluster randomised controlled trial of a school-located obesity prevention programme; the Healthy Lifestyles Programme (HeLP) trial. BMC Public Health. 2017. 17:291 DOI: 10.1186/s12889-017-4196-9
  17. Fairclough SJ, Dumuid D, et al. Fitness, fatness and the reallocation of time between children’s daily movement behaviours: an analysis of compositional data. International Journal of Behavioral Nutrition and Physical Activity. 2017. 14:64 DOI:10.1186/s12966-017-0521-z
  18. Noonan RJ, Fairclough SJ, et al. Context matters! sources of variability in weekend physical activity among families: a repeated measures study, BMC Public Health. 2017 April, doi: 10.1186/s12889-017-4232-9
  19. Ramirez et al. Physical activity levels objectively measured among older adults: a population-based study in a Southern city of Brazil. Int J Behav Nutr Phys Act. 2017; 14: 13. doi: 10.1186/s12966-017-0465-3
  20. Menai M, van Hees VT, et al. Accelerometer assessed moderate-to-vigorous physical activity and successful ageing: results from the Whitehall II study. Scientific Reports. 2017 Apr 3;8:45772. doi: 10.1038/srep45772.
  21. Bradley AJ, Webb-Mitchell R, et al Sleep and circadian rhythm disturbance in bipolar disorder. Psychological Medicine 2017 Fenbruary, DOI: 10.1017/S0033291717000186
  22. Knuth AG et al. Objectively-measured physical activity in children is influenced by social indicators rather than biological lifecourse factors: Evidence from a Brazilian cohort. Prev Med. 2017 April. 97:40-40 doi: 10.1016/j.ypmed.2016.12.051.
  23. Afshar et al. Changes in physical activity after bariatric surgery: using objective and self-reported measures. Surg Obes Relat Dis. 2017 March. doi: 10.1016/j.soard.2016.09.012.
  24. Rowlands A V, Mirkes EM, et al. (2017). Accelerometer-assessed Physical Activity in Epidemiology: Are Monitors Equivalent? Medicine and Science in Sport and Exercise doi: 10.1249/MSS.0000000000001435.
  25. Ellis K, Kerr J, et al. Hip and Wrist Accelerometer Algorithms for Free-Living Behavior Classification. Medicine and Science in Sport and Exercise (2017) doi: 10.1249/MSS.0000000000000840.

2016

  1. Duncan MJ et al. Balanced: a randomised trial examining the efficacy of two self-monitoring methods for an app-basedmulti-behaviour intervention to improve physical activity, sitting and sleep in adults. BMC Public Health. 2016 Jul 30;16:670. doi: 10.1186/s12889–016–3256-x.
  2. Charman et al The effect of percutaneous coronary intervention on habitual physical activity in older patients. BMC Cardiovasc Disord. 2016 Dec 3;16(1):248.
  3. Hiden et al Prediction of workflow execution time using provenance traces: practical applications in medical data processing. IEEE eScience Conference, Baltimore 2016
  4. Fairclough SJ et al Wear Compliance and Activity in Children Wearing Wrist- and Hip-Mounted Accelerometers. Med Sci Sports Exerc. 2016 Feb;48(2):245–53. doi: 10.1249/MSS.0000000000000771.
  5. Bakrania K, Thomas Yates T, et al. Intensity Thresholds on Raw Acceleration Data: Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD) Approaches. PLOS ONE, 2016, doi: 10.1371/journal.pone.0164045

2015

  1. Bell, J. A. et al. Healthy obesity and objective physical activity. Am. J. Clin. Nutr. 2015. doi:10.3945/ajcn.115.110924
  2. Esteban-Cornejo, I. et al. Physical Activity throughout Adolescence and Cognitive Performance at 18 Years of Age. Med. Sci. Sports Exerc. 2015. 47, 2552–7.
  3. Horta, B. L. et al. Objectively measured physical activity and sedentary-time are associated with arterial stiffness in Brazilian young adults. Atherosclerosis. 2015. 243, 148–54.
  4. Sabia, S. et al. Physical Activity and Adiposity Markers at Older Ages: Accelerometer Vs Questionnaire Data. J. Am. Med. Dir. Assoc. 16, 438.e7–438.e13 (2015).

2014

  1. da Silva, I. C. et al. Physical activity levels in three Brazilian birth cohorts as assessed with raw triaxial wrist accelerometry. Int. J. Epidemiol. 2014. Dec;43(6):1959-68. doi: 10.1093/ije/dyu203.
  2. Sabia, S. et al. Association Between Questionnaire- and Accelerometer-Assessed Physical Activity: The Role of Sociodemographic Factors. Am. J. Epidemiol. 2014. doi:10.1093/aje/kwt330

Academic publications contributing to the development and/or evaluation of algorithms included in GGIR:

  1. van Hees et al. Estimation of daily energy expenditure in pregnant and non-pregnant women using a wrist-worn tri-axial accelerometer. 2011 ;6(7):e22922. doi: 10.1371/journal.pone.0022922.
  2. van Hees et al. Separating movement and gravity components in an acceleration signal and implications for the assessment of human daily physical activity. PLoS One. 2013 Apr 23;8(4):e61691. doi: 10.1371/journal.pone.0061691.
  3. Hildebrand M et al. Age group comparability of raw accelerometer output from wrist- and hip-worn monitors. Med Sci Sports Exerc. 2014 Sep;46(9):1816–24. doi: 10.1249/MSS.0000000000000289.
  4. van Hees et al. Autocalibration of accelerometer data for free-living physical activity assessment using local gravity and temperature: an evaluation on four continents. J Appl Physiol. 2014 Oct 1;117(7):738–44.
  5. van Hees et al. A Novel, Open Access Method to Assess Sleep Duration Using a Wrist-Worn Accelerometer. PLoS One. 2015 Nov 16;10(11):e0142533. doi: 10.1371/journal.pone.0142533. eCollection 2015.
  6. Hildebrand M et al. Evaluation of raw acceleration sedentary thresholds in children and adults. Scand J Med Sci Sports. 2016 Nov 22. doi: 10.1111/sms.12795.
  7. Rowlands AV et al. Raw Accelerometer Data Analysis with GGIR R-package: Does Accelerometer Brand Matter? Med Sci Sports Exerc. 2016 Oct;48(10):1935–41
  8. Rowlands, A.V. et al (2016). Moving forward with backwards compatibility: Translating wrist accelerometer data. Medicine and Science in Sport and Exercise doi: 10.1249/MSS.0000000000001015
  9. van Hees VT, Sabia S, et al. Estimating sleep parameters using an accelerometer without sleep diary. Scientific Reports 2018. doi: 10.1038/s41598-018-31266-z.
  10. van Kuppevelt D, Heywood J, et al. Segmenting accelerometer data from daily life with unsupervised machine learning. PLoSONE, 2019. doi: 10.1371/journal.pone.0208692
  11. Ahmadi MN, Nathan N, et al. Non-wear or sleep? Evaluation of five non-wear detection algorithms for raw accelerometer data. J of Sports Science. 2020. doi: 10.1080/02640414.2019.1703301

Papers that used a partial replication of GGIR in a different programming language:

  1. Doherty A et al. Large Scale Population Assessment of Physical Activity Using Wrist Worn Accelerometers: The UK Biobank Study. PLoSONE. 2017 Feb 1;12(2):e0169649. doi: 10.1371/journal.pone.0169649
Clone this wiki locally