Honghuang Lin1, Mayank Sardana2, Yuankai Zhang3, Chunyu Liu3, Ludovic Trinquart3, Emelia J Benjamin4,5, Emily S Manders4, Kelsey Fusco4, Jelena Kornej4, Michael M Hammond4, Nicole L Spartano6, Chathurangi H Pathiravasan3, Vik Kheterpal7, Chris Nowak7, Belinda Borrelli8, Joanne M Murabito9,4, David D McManus10,11. 1. Section of Computational Biomedicine, Department of Medicine (H.L.), Boston University School of Medicine, MA. 2. Cardiology Division, Department of Medicine, University of California San Francisco (M.S.). 3. Department of Biostatistics, Boston University School of Public Health, MA (Y.Z., C.L., L.T., C.H.P.). 4. Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, MA (H.L., E.J.B., E.S.M., K.F., J.K., M.M.H., J.M.M.). 5. Section of Preventive Medicine and Epidemiology and Cardiovascular Medicine, Departments of Medicine and Epidemiology, Boston University Schools of Medicine and Public Health, MA (E.J.B.). 6. Section of Endocrinology, Diabetes, Nutrition, and Weight Management (N.L.S.), Boston University School of Medicine, MA. 7. Care Evolution, Ann Arbor, MI (V.K., C.N.). 8. Henry M. Goldman School of Dental Medicine, Center for Behavioral Science Research, Department of Health Policy & Health Services Research, Boston University, MA (B.B.). 9. Section of General Internal Medicine, Department of Medicine (J.M.M.), Boston University School of Medicine, MA. 10. Cardiology Division, Department of Medicine (D.D.M.), University of Massachusetts Medical School, Worcester. 11. Department of Quantitative Health Sciences (D.D.M.), University of Massachusetts Medical School, Worcester.
Abstract
RATIONALE: A sedentary lifestyle is associated with increased risk for cardiovascular disease (CVD). Smartwatches enable accurate daily activity monitoring for physical activity measurement and intervention. Few studies, however, have examined physical activity measures from smartwatches in relation to traditional risk factors associated with future risk for CVD. OBJECTIVE: To investigate the association of habitual physical activity measured by smartwatch with predicted CVD risk in adults. METHODS AND RESULTS: We enrolled consenting FHS (Framingham Heart Study) participants in an ongoing eFHS (electronic Framingham Heart Study) at the time of their FHS research center examination. We provided participants with a smartwatch (Apple Watch Series 0) and instructed them to wear it daily, which measured their habitual physical activity as the average daily step count. We estimated the 10-year predicted risk of CVD using the American College of Cardiology/American Heart Association 2013 pooled cohort risk equation. We estimated the association between physical activity and predicted risk of CVD using linear mixed effects models adjusting for age, sex, wear time, and familial structure. Our study included 903 eFHS participants (mean age 53±9 years, 61% women, 9% non-White) who wore the smartwatch ≥5 hours per day for ≥30 days. Median daily step count was similar among men (7202 with interquartile range 3619) and women (7260 with interquartile range 3068; P=0.52). Average 10-year predicted CVD risk was 4.5% (interquartile range, 6.1%) for men and 1.2% (interquartile range, 2.2%) for women (P=1.3×10-26). Every 1000 steps higher habitual physical activity was associated with 0.18% lower predicted CVD risk (P=3.2×10-4). The association was attenuated but remained significant after further adjustment for body mass index (P=0.01). CONCLUSIONS: In this community-based sample of adults, higher daily physical activity measured by a study smartwatch was associated with lower predicted risk of CVD. Future research should examine the longitudinal association of prospectively measured daily activity and incident CVD.
RATIONALE: A sedentary lifestyle is associated with increased risk for cardiovascular disease (CVD). Smartwatches enable accurate daily activity monitoring for physical activity measurement and intervention. Few studies, however, have examined physical activity measures from smartwatches in relation to traditional risk factors associated with future risk for CVD. OBJECTIVE: To investigate the association of habitual physical activity measured by smartwatch with predicted CVD risk in adults. METHODS AND RESULTS: We enrolled consenting FHS (Framingham Heart Study) participants in an ongoing eFHS (electronic Framingham Heart Study) at the time of their FHS research center examination. We provided participants with a smartwatch (Apple Watch Series 0) and instructed them to wear it daily, which measured their habitual physical activity as the average daily step count. We estimated the 10-year predicted risk of CVD using the American College of Cardiology/American Heart Association 2013 pooled cohort risk equation. We estimated the association between physical activity and predicted risk of CVD using linear mixed effects models adjusting for age, sex, wear time, and familial structure. Our study included 903 eFHS participants (mean age 53±9 years, 61% women, 9% non-White) who wore the smartwatch ≥5 hours per day for ≥30 days. Median daily step count was similar among men (7202 with interquartile range 3619) and women (7260 with interquartile range 3068; P=0.52). Average 10-year predicted CVD risk was 4.5% (interquartile range, 6.1%) for men and 1.2% (interquartile range, 2.2%) for women (P=1.3×10-26). Every 1000 steps higher habitual physical activity was associated with 0.18% lower predicted CVD risk (P=3.2×10-4). The association was attenuated but remained significant after further adjustment for body mass index (P=0.01). CONCLUSIONS: In this community-based sample of adults, higher daily physical activity measured by a study smartwatch was associated with lower predicted risk of CVD. Future research should examine the longitudinal association of prospectively measured daily activity and incident CVD.
Entities:
Keywords:
adult; body mass index; exercise; primary prevention; risk factor
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