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Vincent van Hees edited this page May 18, 2020 · 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 Occassionally we come across publications where authors do not cite the GGIR software when GGIR is used.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.

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

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: 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. Khan M, Bell R, et al. Effects of a School Based Intervention on Children’s Physical Activity and Healthy Eating: A Mixed-Methods Study. Env Res and Public Health 2019. doi: 10.3390/ijerph16224320
  44. 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
  45. 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
  46. 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
  47. 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
  48. 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
  49. 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
  50. 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
  51. 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
  52. 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
  53. 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
  54. Acosta FM, Sanchez-Delgao G, 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 Research Society 2019. doi: 10.1093/sleep/zsz177
  55. 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.
  56. 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
  57. Zhu G, Catt M, et al. Objective sleep assessment in >80,000 UK mid-life adults: Associations with sociodemographic characteristics, physical activity and caffeine. PLoSONE 2019. doi: 10.1371/journal.pone.0226220
  58. 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
  59. 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
  60. 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
  61. 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. Dallosso H., 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. Trials, 2018. doi: 10.1186/s13063-018-2939-2
  17. 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.
  18. 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
  19. 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
  20. 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
  21. 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
  22. 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
  23. 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
  24. 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
  25. 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
  26. 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
  27. Stiles V, Pearce M, et al. Wrist-worn Accelerometry for Runners: Objective Quantification of Training Load. MSSE 2018, doi: 10.1249/MSS.0000000000001704
  28. 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
  29. 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
  30. 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.
  31. 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
  32. Horne S, Hay K et al. An evaluation of sleep disturbance on in-patient psychiatric units in the UK. BJPsych Bulletin, 2018, doi: 10.1192/bjb.2018.42
  33. 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
  34. 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
  35. 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
  36. 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
  37. 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
  38. 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
  39. 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
  40. 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
  41. 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)
  42. 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
  43. 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
  44. 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
  45. 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
  46. 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
  47. 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
  48. Hurter L., Fairclough SJ, et al. Establishing Raw Acceleration Thresholds to Classify Sedentary and Stationary Behaviour in Children. children, 2018. doi: 10.3390/children5120172
  49. Kerr J, Marinac CR et al. Comparison of Accelerometry Methods for Estimating Physical Activity, Med Sci Sports Exerc. 2017. doi: 10.1249/MSS.0000000000001124
  50. 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
  51. 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
  52. 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
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