Show simple item record

dc.contributor.authorZhang, Yuankai
dc.contributor.authorPathiravasan, Chathurangi H
dc.contributor.authorHammond, Michael M
dc.contributor.authorLiu, Hongshan
dc.contributor.authorLin, Honghuang
dc.contributor.authorSardana, Mayank
dc.contributor.authorTrinquart, Ludovic
dc.contributor.authorBorrelli, Belinda
dc.contributor.authorManders, Emily S
dc.contributor.authorKornej, Jelena
dc.contributor.authorSpartano, Nicole L
dc.contributor.authorNowak, Christopher
dc.contributor.authorKheterpal, Vik
dc.contributor.authorBenjamin, Emelia J
dc.contributor.authorMcManus, David D
dc.contributor.authorMurabito, Joanne M
dc.contributor.authorLiu, Chunyu
dc.date.accessioned2023-06-27T14:21:04Z
dc.date.available2023-06-27T14:21:04Z
dc.date.issued2022-01-07
dc.identifier.citationZhang Y, Pathiravasan CH, Hammond MM, Liu H, Lin H, Sardana M, Trinquart L, Borrelli B, Manders ES, Kornej J, Spartano NL, Nowak C, Kheterpal V, Benjamin EJ, McManus DD, Murabito JM, Liu C. Comparison of Daily Routines Between Middle-aged and Older Participants With and Those Without Diabetes in the Electronic Framingham Heart Study: Cohort Study. JMIR Diabetes. 2022 Jan 7;7(1):e29107. doi: 10.2196/29107. PMID: 34994694; PMCID: PMC8783285.en_US
dc.identifier.eissn2371-4379
dc.identifier.doi10.2196/29107en_US
dc.identifier.pmid34994694
dc.identifier.urihttp://hdl.handle.net/20.500.14038/52188
dc.description.abstractBackground: Daily routines (eg, physical activity and sleep patterns) are important for diabetes self-management. Traditional research methods are not optimal for documenting long-term daily routine patterns in participants with glycemic conditions. Mobile health offers an effective approach for collecting users' long-term daily activities and analyzing their daily routine patterns in relation to diabetes status. Objective: This study aims to understand how routines function in diabetes self-management. We evaluate the associations of daily routine variables derived from a smartwatch with diabetes status in the electronic Framingham Heart Study (eFHS). Methods: The eFHS enrolled the Framingham Heart Study participants at health examination 3 between 2016 and 2019. At baseline, diabetes was defined as fasting blood glucose level ≥126 mg/dL or as a self-report of taking a glucose-lowering medication; prediabetes was defined as fasting blood glucose level of 100-125 mg/dL. Using smartwatch data, we calculated the average daily step counts and estimated the wake-up times and bedtimes for the eFHS participants on a given day. We compared the average daily step counts and the intraindividual variability of the wake-up times and bedtimes of the participants with diabetes and prediabetes with those of the referents who were neither diabetic nor prediabetic, adjusting for age, sex, and race or ethnicity. Results: We included 796 participants (494/796, 62.1% women; mean age 52.8, SD 8.7 years) who wore a smartwatch for at least 10 hours/day and remained in the study for at least 30 days after enrollment. On average, participants with diabetes (41/796, 5.2%) took 1611 fewer daily steps (95% CI 863-2360; P<.001) and had 12 more minutes (95% CI 6-18; P<.001) in the variation of their estimated wake-up times, 6 more minutes (95% CI 2-9; P=.005) in the variation of their estimated bedtimes compared with the referents (546/796, 68.6%) without diabetes or prediabetes. Participants with prediabetes (209/796, 26.2%) also walked fewer daily steps (P=.04) and had a larger variation in their estimated wake-up times (P=.04) compared with the referents. Conclusions: On average, participants with diabetes at baseline walked significantly fewer daily steps and had larger variations in their wake-up times and bedtimes than the referent group. These findings suggest that modifying the routines of participants with poor glycemic health may be an important approach to the self-management of diabetes. Future studies should be designed to improve the remote monitoring and self-management of diabetes.en_US
dc.language.isoenen_US
dc.relation.ispartofJMIR Diabetesen_US
dc.relation.urlhttps://doi.org/10.2196/29107en_US
dc.rights©Yuankai Zhang, Chathurangi H Pathiravasan, Michael M Hammond, Hongshan Liu, Honghuang Lin, Mayank Sardana, Ludovic Trinquart, Belinda Borrelli, Emily S Manders, Jelena Kornej, Nicole L Spartano, Christopher Nowak, Vik Kheterpal, Emelia J Benjamin, David D McManus, Joanne M Murabito, Chunyu Liu. Originally published in JMIR Diabetes (https://diabetes.jmir.org), 07.01.2022. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Diabetes, is properly cited. The complete bibliographic information, a link to the original publication on https://diabetes.jmir.org/, as well as this copyright and license information must be included.en_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectdaily physical activitiesen_US
dc.subjectdaily routine patternen_US
dc.subjectdiabetesen_US
dc.subjectdiabetes self-managementen_US
dc.subjectmobile healthen_US
dc.subjectmobile phoneen_US
dc.subjectsleepen_US
dc.subjectsmartwatchen_US
dc.subjectstep countsen_US
dc.titleComparison of Daily Routines Between Middle-aged and Older Participants With and Those Without Diabetes in the Electronic Framingham Heart Study: Cohort Studyen_US
dc.typeJournal Articleen_US
dc.source.journaltitleJMIR diabetes
dc.source.volume7
dc.source.issue1
dc.source.beginpagee29107
dc.source.endpage
dc.source.countryUnited States
dc.source.countryUnited States
dc.source.countryUnited States
dc.source.countryUnited States
dc.source.countryUnited States
dc.source.countryUnited States
dc.source.countryUnited States
dc.source.countryUnited States
dc.source.countryUnited States
dc.source.countryCanada
dc.identifier.journalJMIR diabetes
refterms.dateFOA2023-06-27T14:21:05Z
dc.contributor.departmentMedicineen_US
dc.contributor.departmentPopulation and Quantitative Health Sciencesen_US


Files in this item

Thumbnail
Name:
document.pdf
Size:
422.4Kb
Format:
PDF

This item appears in the following Collection(s)

Show simple item record

©Yuankai Zhang, Chathurangi H Pathiravasan, Michael M Hammond, Hongshan Liu, Honghuang Lin, Mayank Sardana, Ludovic
Trinquart, Belinda Borrelli, Emily S Manders, Jelena Kornej, Nicole L Spartano, Christopher Nowak, Vik Kheterpal, Emelia J
Benjamin, David D McManus, Joanne M Murabito, Chunyu Liu. Originally published in JMIR Diabetes (https://diabetes.jmir.org),
07.01.2022. This is an open-access article distributed under the terms of the Creative Commons Attribution License
(https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium,
provided the original work, first published in JMIR Diabetes, is properly cited. The complete bibliographic information, a link
to the original publication on https://diabetes.jmir.org/, as well as this copyright and license information must be included.
Except where otherwise noted, this item's license is described as ©Yuankai Zhang, Chathurangi H Pathiravasan, Michael M Hammond, Hongshan Liu, Honghuang Lin, Mayank Sardana, Ludovic Trinquart, Belinda Borrelli, Emily S Manders, Jelena Kornej, Nicole L Spartano, Christopher Nowak, Vik Kheterpal, Emelia J Benjamin, David D McManus, Joanne M Murabito, Chunyu Liu. Originally published in JMIR Diabetes (https://diabetes.jmir.org), 07.01.2022. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Diabetes, is properly cited. The complete bibliographic information, a link to the original publication on https://diabetes.jmir.org/, as well as this copyright and license information must be included.