Understanding activity and physiology at scale: The Apple Heart & Movement Study.
Journal
NPJ digital medicine
ISSN: 2398-6352
Titre abrégé: NPJ Digit Med
Pays: England
ID NLM: 101731738
Informations de publication
Date de publication:
10 Sep 2024
10 Sep 2024
Historique:
received:
16
11
2023
accepted:
03
07
2024
medline:
11
9
2024
pubmed:
11
9
2024
entrez:
10
9
2024
Statut:
epublish
Résumé
Physical activity or structured exercise is beneficial in a wide range of circumstances. Nevertheless, individual-level data on differential responses to various types of activity are not yet sufficient in scale, duration or level of annotation to understand the mechanisms of discrete outcomes nor to support personalized recommendations. The Apple Heart & Movement Study was designed to passively collect the dense physiologic data accessible on Apple Watch and iPhone from a large real-world cohort distributed across the US in order to address these knowledge gaps.
Identifiants
pubmed: 39256546
doi: 10.1038/s41746-024-01187-5
pii: 10.1038/s41746-024-01187-5
doi:
Types de publication
Journal Article
Langues
eng
Pagination
242Informations de copyright
© 2024. The Author(s).
Références
Arnett, D. K. et al. 2019 ACC/AHA guideline on the primary prevention of cardiovascular disease: executive summary: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J. Am. Coll. Cardiol. 74, 1376–1414 (2019).
doi: 10.1016/j.jacc.2019.03.009
pubmed: 30894319
pmcid: 8344373
Khurshid, S. et al. Wearable accelerometer-derived physical activity and incident disease. NPJ Digit Med. 5, 131 (2022).
doi: 10.1038/s41746-022-00676-9
pubmed: 36056190
pmcid: 9440134
Master, H. et al. Association of step counts over time with the risk of chronic disease in the All of Us Research Program. Nat. Med. 28, 2301–2308 (2022).
doi: 10.1038/s41591-022-02012-w
pubmed: 36216933
pmcid: 9671804
Alemany, J. A., Delgado-Diaz, D. C., Mathews, H., Davis, J. M. & Kostek, M. C. Comparison of acute responses to isotonic or isokinetic eccentric muscle action: differential outcomes in skeletal muscle damage and implications for rehabilitation. Int J. Sports Med. 35, 1–7 (2014).
pubmed: 23780898
Ross, L. M., Slentz, C. A. & Kraus, W. E. Evaluating individual level responses to exercise for health outcomes in overweight or obese adults. Front. Physiol. 10, 1401 (2019).
doi: 10.3389/fphys.2019.01401
pubmed: 31798463
pmcid: 6867965
Shigeta, T. T. et al. Cardiorespiratory and muscular fitness associations with older adolescent cognitive control. J. Sport Health Sci. 10, 82–90 (2021).
doi: 10.1016/j.jshs.2020.05.004
pubmed: 32442694
Vidoni, E. D. et al. Dementia risk and dynamic response to exercise: a non-randomized clinical trial. PLoS ONE 17, e0265860 (2022).
doi: 10.1371/journal.pone.0265860
pubmed: 35802628
pmcid: 9269742
Ross, R. et al. Precision exercise medicine: understanding exercise response variability. Br. J. Sports Med. 53, 1141–1153 (2019).
doi: 10.1136/bjsports-2018-100328
pubmed: 30862704
Neufer, P. D. et al. Understanding the cellular and molecular mechanisms of physical activity-induced health benefits. Cell Metab. 22, 4–11 (2015).
doi: 10.1016/j.cmet.2015.05.011
pubmed: 26073496
Roberts, M. D. et al. Physiological differences between low versus high skeletal muscle hypertrophic responders to resistance exercise training: current perspectives and future research directions. Front. Physiol. 9, 834 (2018).
doi: 10.3389/fphys.2018.00834
pubmed: 30022953
pmcid: 6039846
Mahalingaiah, S. et al. Design and methods of the Apple Women’s Health Study: a digital longitudinal cohort study. Am. J. Obstet. Gynecol. 226, 545 e541–545.e529 (2022).
doi: 10.1016/j.ajog.2021.09.041
Neitzel, R. L. et al. Toward a better understanding of nonoccupational sound exposures and associated health impacts: Methods of the Apple Hearing Study. J. Acoust. Soc. Am. 151, 1476 (2022).
doi: 10.1121/10.0009620
pubmed: 35364926
Chen, T. C., Clark, J., Riddles, M. K., Mohadjer, L. K. & Fakhouri, T. H. I. National Health and Nutrition Examination Survey, 2015-2018: sample design and estimation procedures. Vital-. Health Stat. 2, 1–35 (2020).
All of Us Research Program, I. et al. The “All of Us” research program. N. Engl. J. Med. 381, 668–676 (2019).
doi: 10.1056/NEJMsr1809937
Lohman, M. C. et al. Operationalisation and validation of the Stopping Elderly Accidents, Deaths, and Injuries (STEADI) fall risk algorithm in a nationally representative sample. J. Epidemiol. Community Health 71, 1191–1197 (2017).
doi: 10.1136/jech-2017-209769
pubmed: 28947669
Saunders, J. B., Aasland, O. G., Babor, T. F., de la Fuente, J. R. & Grant, M. Development of the alcohol use disorders identification test (AUDIT): WHO collaborative project on early detection of persons with harmful alcohol consumption-II. Addiction 88, 791–804 (1993).
doi: 10.1111/j.1360-0443.1993.tb02093.x
pubmed: 8329970
Ware, J., Jr. Kosinski, M. & Keller, S. D. A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity. Med. Care 34, 220–233 (1996).
Rosow, I. & Breslau, N. A Guttman health scale for the aged. J. Gerontol. 21, 556–559 (1966).
doi: 10.1093/geronj/21.4.556
pubmed: 5918309
Cohen, B. G., Colligan, M. J., Wester, W. 2nd & Smith, M. J. An investigation of job satisfaction factors in an incident of mass psychogenic illness at the workplace. Occup. Health Nurs. 26, 10–16 (1978).
doi: 10.1177/216507997802600102
pubmed: 564008
Andrews, G., Kemp, A., Sunderland, M., Von Korff, M. & Ustun, T. B. Normative data for the 12 item WHO Disability Assessment Schedule 2.0. PLoS ONE 4, e8343 (2009).
doi: 10.1371/journal.pone.0008343
pubmed: 20020047
pmcid: 2791224
Adler, N. E., Epel, E. S., Castellazzo, G. & Ickovics, J. R. Relationship of subjective and objective social status with psychological and physiological functioning: preliminary data in healthy white women. Health Psychol. 19, 586–592 (2000).
doi: 10.1037/0278-6133.19.6.586
pubmed: 11129362