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Comparison of Daily Routines Between Middle-aged and Older Participants With and Those Without Diabetes in the Electronic Framingham Heart Study: Cohort Study.
Zhang, Yuankai; Pathiravasan, Chathurangi H; Hammond, Michael M; Liu, Hongshan; Lin, Honghuang; Sardana, Mayank; Trinquart, Ludovic; Borrelli, Belinda; Manders, Emily S; Kornej, Jelena; Spartano, Nicole L; Nowak, Christopher; Kheterpal, Vik; Benjamin, Emelia J; McManus, David D; Murabito, Joanne M; Liu, Chunyu.
Afiliação
  • Zhang Y; Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States.
  • Pathiravasan CH; Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States.
  • Hammond MM; Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States.
  • Liu H; Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States.
  • Lin H; Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, United States.
  • Sardana M; Cardiology Division, Department of Medicine, University of California San Francisco, San Francisco, CA, United States.
  • Trinquart L; Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States.
  • Borrelli B; Center for Behavioral Science Research, Henry M. Goldman School of Dental Medicine, Boston University, Boston, MA, United States.
  • Manders ES; Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States.
  • Kornej J; Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States.
  • Spartano NL; Section of Endocrinology, Diabetes, Nutrition, and Weight Management, Boston University School of Medicine, Boston, MA, United States.
  • Nowak C; Care Evolution, Ann Arbor, MI, United States.
  • Kheterpal V; Care Evolution, Ann Arbor, MI, United States.
  • Benjamin EJ; Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States.
  • McManus DD; Section of Preventive Medicine and Epidemiology and Cardiovascular Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, United States.
  • Murabito JM; Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States.
  • Liu C; Cardiology Division, Department of Medicine, University of Massachusetts Medical School, Worcester, MA, United States.
JMIR Diabetes ; 7(1): e29107, 2022 Jan 07.
Article em En | MEDLINE | ID: mdl-34994694
ABSTRACT

BACKGROUND:

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.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article