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Mossavar-Rahmani Y, Lin J, Pan S, Song RJ, Xue X, Spartano NL, Xanthakis V, Sotres-Alvarez D, Marquez DX, Daviglus M, Carlson JA, Parada H, Evenson KR, Talavera AC, Gellman M, Perreira KM, Gallo LC, Vasan RS, Kaplan RC. Characterizing longitudinal change in accelerometry-based moderate-to-vigorous physical activity in the Hispanic Community Health Study/Study of Latinos and the Framingham Heart Study. BMC Public Health 2023; 23:1614. [PMID: 37620824 PMCID: PMC10464120 DOI: 10.1186/s12889-023-16442-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 08/02/2023] [Indexed: 08/26/2023] Open
Abstract
BACKGROUND Physical activity promotes health and is particularly important during middle and older age for decreasing morbidity and mortality. We assessed the correlates of changes over time in moderate-to-vigorous physical activity (MVPA) in Hispanic/Latino adults from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL: mean [SD] age 49.2 y [11.5]) and compared them to a cohort of primarily White adults from the Framingham Heart Study (FHS: mean [SD] 46.9 y [9.2]). METHODS Between 2008 and 2019, we assessed accelerometry-based MVPA at two time points with an average follow-up of: 7.6 y, SD 1.3 for HCHS/SOL, and 7.8 y, SD 0.7 for FHS. We used multinomial logistic regression to relate socio-demographic and health behaviors with changes in compliance with 2018 US recommendations for MVPA from time 1 to time 2 (remained active or inactive; became active or inactive) across the two cohorts. RESULTS In HCHS/SOL mean MVPA was 22.6 (SD, 23.8) minutes at time 1 and dropped to 16.7 (19.0) minutes at time 2. In FHS Mean MVPA was 21.7 min (SD, 17.7) at time 1 and dropped to 21.3 min (SD, 19.2) at time 2. Across both cohorts, odds of meeting MVPA guidelines over time were about 6% lower in individuals who had lower quality diets vs. higher, about half in older vs. younger adults, about three times lower in women vs. men, and 9% lower in individuals who had a higher vs. lower BMI at baseline. Cohorts differed in how age, gender, income, education, depressive symptoms, marital status and perception of general health and pain associated with changes in physical activity. High income older Hispanics/Latino adults were more likely to become inactive at the follow-up visit as were HCHS/SOL women who were retired and FHS participants who had lower levels of education and income. Higher depressive symptomology was associated with becoming active only in HCHS/SOL women. Being male and married was associated with becoming inactive in both cohorts. Higher perception of general health and lower perception of pain were associated with remaining active only in FHS adults. CONCLUSIONS These findings highlight potentially high-risk groups for targeted MVPA intervention.
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Affiliation(s)
- Yasmin Mossavar-Rahmani
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Belfer Bldg, 1312C, Bronx, NY, 10461, USA.
| | - Juan Lin
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Belfer Bldg, 1312C, Bronx, NY, 10461, USA
| | - Stephanie Pan
- Section of Preventive Medicine and Epidemiology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA
| | - Rebecca J Song
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Xiaonan Xue
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Belfer Bldg, 1312C, Bronx, NY, 10461, USA
| | - Nicole L Spartano
- Department of Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA
| | - Vanessa Xanthakis
- Section of Preventive Medicine and Epidemiology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA
- Framingham Heart Study, Framingham, MA, 01701, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Daniela Sotres-Alvarez
- Department of Biostatistics, Gillings School of Global Public Health, Collaborative Studies Coordinating Center, University of North Carolina, Chapel Hill, NC, 27516, USA
| | - David X Marquez
- Department of Kinesiology & Nutrition, University of Illinois Chicago, Chicago, IL, 60612, USA
| | - Martha Daviglus
- Institute for Minority Health Research, University of Illinois Chicago, Chicago, IL, 60612, USA
| | - Jordan A Carlson
- Department of Pediatrics, Children's Mercy Hospital and University of Missouri-Kansas City School of Medicine, Kansas City, MO, 64108, USA
| | - Humberto Parada
- Division of Epidemiology & Biostatistics, San Diego State University School of Public Health, San Diego, CA, 92182, USA
| | - Kelly R Evenson
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Ana C Talavera
- South Bay Latino Research Center, College of Sciences, San Diego State University, San Diego, CA, 92182, USA
| | - Marc Gellman
- Department of Psychology, University of Miami, Coral Gables, Florida, 33136, USA
| | - Krista M Perreira
- Department of Social Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, 27599, USA
| | - Linda C Gallo
- Department of Psychology, San Diego State University, San Diego, CA, 91910, USA
| | - Ramachandran S Vasan
- Section of Preventive Medicine and Epidemiology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, 02118, USA
- Framingham Heart Study, Framingham, MA, 01701, USA
- University of Texas School of Public Health, San Antonio and University of Texas Health Science Center, San Antonio, TX, 78229, USA
- Section of Cardiovascular Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA
| | - Robert C Kaplan
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Belfer Bldg, 1312C, Bronx, NY, 10461, USA
- Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, Seattle, WA, 98109, USA
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Wang X, Pathiravasan CH, Zhang Y, Trinquart L, Borrelli B, Spartano NL, Lin H, Nowak C, Kheterpal V, Benjamin EJ, McManus DD, Murabito JM, Liu C. Association of Depressive Symptom Trajectory With Physical Activity Collected by mHealth Devices in the Electronic Framingham Heart Study: Cohort Study. JMIR Ment Health 2023; 10:e44529. [PMID: 37450333 PMCID: PMC10382951 DOI: 10.2196/44529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 06/02/2023] [Accepted: 06/05/2023] [Indexed: 07/18/2023] Open
Abstract
BACKGROUND Few studies have examined the association between depressive symptom trajectories and physical activity collected by mobile health (mHealth) devices. OBJECTIVE We aimed to investigate if antecedent depressive symptom trajectories predict subsequent physical activity among participants in the electronic Framingham Heart Study (eFHS). METHODS We performed group-based multi-trajectory modeling to construct depressive symptom trajectory groups using both depressive symptoms (Center for Epidemiological Studies-Depression [CES-D] scores) and antidepressant medication use in eFHS participants who attended 3 Framingham Heart Study research exams over 14 years. At the third exam, eFHS participants were instructed to use a smartphone app for submitting physical activity index (PAI) surveys. In addition, they were provided with a study smartwatch to track their daily step counts. We performed linear mixed models to examine the association between depressive symptom trajectories and physical activity including app-based PAI and smartwatch-collected step counts over a 1-year follow-up adjusting for age, sex, wear hour, BMI, smoking status, and other health variables. RESULTS We identified 3 depressive symptom trajectory groups from 722 eFHS participants (mean age 53, SD 8.5 years; n=432, 60% women). The low symptom group (n=570; mean follow-up 287, SD 109 days) consisted of participants with consistently low CES-D scores, and a small proportion reported antidepressant use. The moderate symptom group (n=71; mean follow-up 280, SD 118 days) included participants with intermediate CES-D scores, who showed the highest and increasing likelihood of reporting antidepressant use across 3 exams. The high symptom group (n=81; mean follow-up 252, SD 116 days) comprised participants with the highest CES-D scores, and the proportion of antidepressant use fell between the other 2 groups. Compared to the low symptom group, the high symptom group had decreased PAI (mean difference -1.09, 95% CI -2.16 to -0.01) and the moderate symptom group walked fewer daily steps (823 fewer, 95% CI -1421 to -226) during the 1-year follow-up. CONCLUSIONS Antecedent depressive symptoms or antidepressant medication use was associated with lower subsequent physical activity collected by mHealth devices in eFHS. Future investigation of interventions to improve mood including via mHealth technologies to help promote people's daily physical activity is needed.
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Affiliation(s)
- Xuzhi Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | | | - Yuankai Zhang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Ludovic Trinquart
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
- Tufts Clinical and Translational Science Institute, Tufts University, Boston, MA, United States
- Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, United States
| | - Belinda Borrelli
- Center for Behavioral Science Research, Boston University Henry M Goldman School of Dental Medicine, Boston, MA, United States
| | - Nicole L Spartano
- Section of Endocrinology, Diabetes, Nutrition, and Weight Management, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, United States
| | - Honghuang Lin
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | | | | | - Emelia J Benjamin
- Section of Preventive Medicine and Epidemiology and Cardiovascular Medicine, Department of Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, United States
- Framingham Heart Study, Boston University and National Heart, Lung, and Blood Institute, Framingham, MA, United States
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States
| | - David D McManus
- Cardiology Division, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States
- Department of Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | - Joanne M Murabito
- Framingham Heart Study, Boston University and National Heart, Lung, and Blood Institute, Framingham, MA, United States
- Section of General Internal Medicine, Department of Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, United States
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
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Abstract
Despite improvements in cardiovascular care in recent decades, cardiovascular disease (CVD) remains a leading cause of death worldwide. At its core, CVD is a largely preventable disease with diligent risk factor management and early detection. As highlighted in the American Heart Association's Life's Essential 8, physical activity plays a central role in CVD prevention at an individual and population level. Despite pervasive knowledge of the numerous cardiovascular and noncardiovascular health benefits of physical activity, physical activity has steadily decreased over time and unfavorable changes in physical activity occur throughout people's lives. Here, we use a lifecourse framework to examine the evidence reporting on the association of physical activity with CVD. From in utero to older adults, we review and discuss the evidence detailing how physical activity may prevent incident CVD and mitigate CVD-related morbidity and death across all life stages.
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Affiliation(s)
- Andrew S. Perry
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Erin E. Dooley
- Department of Epidemiology, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Hiral Master
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Nicole L. Spartano
- Section of Endocrinology, Diabetes, Nutrition, and Weight Management, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Evan L. Brittain
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Kelley Pettee Gabriel
- Department of Epidemiology, The University of Alabama at Birmingham, Birmingham, AL, USA
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Shapira-Daniels A, Kornej J, Spartano NL, Wang X, Zhang Y, Pathiravasan CH, Liu C, Trinquart L, Borrelli B, McManus DD, Murabito JM, Benjamin EJ, Lin H. Step Count, Self-reported Physical Activity, and Predicted 5-Year Risk of Atrial Fibrillation: Cross-sectional Analysis. J Med Internet Res 2023; 25:e43123. [PMID: 36877540 PMCID: PMC10028513 DOI: 10.2196/43123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 11/24/2022] [Accepted: 11/30/2022] [Indexed: 03/07/2023] Open
Abstract
BACKGROUND Physical inactivity is a known risk factor for atrial fibrillation (AF). Wearable devices, such as smartwatches, present an opportunity to investigate the relation between daily step count and AF risk. OBJECTIVE The objective of this study was to investigate the association between daily step count and the predicted 5-year risk of AF. METHODS Participants from the electronic Framingham Heart Study used an Apple smartwatch. Individuals with diagnosed AF were excluded. Daily step count, watch wear time (hours and days), and self-reported physical activity data were collected. Individuals' 5-year risk of AF was estimated, using the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)-AF score. The relation between daily step count and predicted 5-year AF risk was examined via linear regression, adjusting for age, sex, and wear time. Secondary analyses examined effect modification by sex and obesity (BMI≥30 kg/m2), as well as the relation between self-reported physical activity and predicted 5-year AF risk. RESULTS We examined 923 electronic Framingham Heart Study participants (age: mean 53, SD 9 years; female: n=563, 61%) who had a median daily step count of 7227 (IQR 5699-8970). Most participants (n=823, 89.2%) had a <2.5% CHARGE-AF risk. Every 1000 steps were associated with a 0.08% lower CHARGE-AF risk (P<.001). A stronger association was observed in men and individuals with obesity. In contrast, self-reported physical activity was not associated with CHARGE-AF risk. CONCLUSIONS Higher daily step counts were associated with a lower predicted 5-year risk of AF, and this relation was stronger in men and participants with obesity. The utility of a wearable daily step counter for AF risk reduction merits further investigation.
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Affiliation(s)
- Ayelet Shapira-Daniels
- Section of General Internal Medicine, Department of Medicine, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, United States
| | - Jelena Kornej
- Boston University's Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, MA, United States
| | - Nicole L Spartano
- Section of Endocrinology, Diabetes, Nutrition and Weight Management, Department of Medicine, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, United States
| | - Xuzhi Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Yuankai Zhang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | | | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Ludovic Trinquart
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Belinda Borrelli
- Center for Behavioral Science Research, Henry M Goldman School of Dental Medicine, Boston University, Boston, MA, United States
| | - David D McManus
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States
- Department of Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | - Joanne M Murabito
- Section of General Internal Medicine, Department of Medicine, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, United States
- Boston University's Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, MA, United States
| | - Emelia J Benjamin
- Boston University's Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, MA, United States
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States
- Section of Cardiovascular Medicine, Department of Medicine, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, United States
| | - Honghuang Lin
- Boston University's Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, MA, United States
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States
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5
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Spartano NL, Wang R, Yang Q, Chernofsky A, Murabito JM, Vasan RS, Levy D, Beiser AS, Seshadri S. Association of Accelerometer-Measured Physical Activity and Sedentary Time with Epigenetic Markers of Aging. Med Sci Sports Exerc 2023; 55:264-272. [PMID: 36107108 PMCID: PMC9840651 DOI: 10.1249/mss.0000000000003041] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
INTRODUCTION/PURPOSE Physical activity may influence chronic disease risk, in part, through epigenetic mechanisms. Previous studies have demonstrated that an acute bout of physical activity can influence DNA methylation status. Few studies have explored the relationship between habitual, accelerometer-measured physical activity or sedentary time with epigenetic markers of aging. METHODS We used linear regression to examine cross-sectional associations of accelerometer-measured physical activity and sedentary time with extrinsic and intrinsic epigenetic age acceleration (EEAA and IEAA) models and GrimAge measured from blood samples from Framingham Heart Study participants with accelerometry and DNA methylation data ( n = 2435; mean age, 54.9 ± 14.3; 46.0% men). Residuals of Hannum-, Horvath-, and GrimAge-predicted epigenetic age were calculated by regressing epigenetic age on chronological age. We took into account blood cell composition for EEAA, IEAA, and AdjGrimAge. Moderate to vigorous physical activity was log-transformed to normalize its distribution. Adjustment models accounted for family structure, age, sex, smoking status, cohort-laboratory indicator, and accelerometer wear time. We additionally explored adjustment for body mass index (BMI). RESULTS Walking 1500 more steps per day or spending 3 fewer hours sedentary was associated with >10 months lower GrimAge biological age (or ~1 month lower AdjGrimAge, after adjusting for blood cells, P < 0.05). Every 5 min·d -1 more moderate to vigorous physical activity was associated with 19-79 d of lower GrimAge (4-23 d lower using EEAA or AdjGrimAge, P < 0.01). Adjusting for BMI attenuated these results, but all statistically significant associations with AdjGrimAge remained. CONCLUSIONS Greater habitual physical activity and lower sedentary time were associated with lower epigenetic age, which was partially explained by BMI. Further research should explore whether changes in physical activity influence methylation status and whether those modifications influence chronic disease risk.
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Affiliation(s)
| | - Ruiqi Wang
- Department of Biostatistics, Boston University School of Public Health (BUSPH), Boston, MA
| | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health (BUSPH), Boston, MA
| | - Ariel Chernofsky
- Department of Biostatistics, Boston University School of Public Health (BUSPH), Boston, MA
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Trinquart L, Liu C, McManus DD, Nowak C, Lin H, Spartano NL, Borrelli B, Benjamin EJ, Murabito JM. Increasing Engagement in the Electronic Framingham Heart Study: Factorial Randomized Controlled Trial. J Med Internet Res 2023; 25:e40784. [PMID: 36662544 PMCID: PMC9898831 DOI: 10.2196/40784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 11/02/2022] [Accepted: 12/01/2022] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Smartphone apps and mobile health devices offer innovative ways to collect longitudinal cardiovascular data. Randomized evidence regarding effective strategies to maintain longitudinal engagement is limited. OBJECTIVE This study aimed to evaluate smartphone messaging interventions on remote transmission of blood pressure (BP) and heart rate (HR) data. METHODS We conducted a 2 × 2 × 2 factorial blinded randomized trial with randomization implemented centrally to ensure allocation concealment. We invited participants from the Electronic Framingham Heart Study (eFHS), an e-cohort embedded in the FHS, and asked participants to measure their BP (Withings digital cuff) weekly and wear their smartwatch daily. We assessed 3 weekly notification strategies to promote adherence: personalized versus standard; weekend versus weekday; and morning versus evening. Personalized notifications included the participant's name and were tailored to whether or not data from the prior week were transmitted to the research team. Intervention notification messages were delivered weekly automatically via the eFHS app. We assessed if participants transmitted at least one BP or HR measurement within 7 days of each notification after randomization. Outcomes were adherence to BP and HR transmission at 3 months (primary) and 6 months (secondary). RESULTS Of the 791 FHS participants, 655 (82.8%) were eligible and randomized (mean age 53, SD 9 years; 392/655, 59.8% women; 596/655, 91% White). For the personalized versus standard notifications, 38.9% (126/324) versus 28.8% (94/327) participants sent BP data at 3 months (difference=10.1%, 95% CI 2.9%-17.4%; P=.006), but no significant differences were observed for HR data transmission (212/324, 65.4% vs 209/327, 63.9%; P=.69). Personalized notifications were associated with increased BP and HR data transmission versus standard at 6 months (BP: 107/291, 36.8% vs 66/295, 22.4%; difference=14.4%, 95% CI 7.1- 21.7%; P<.001; HR: 186/281, 66.2% vs 158/281, 56.2%; difference=10%, 95% CI 2%-18%; P=.02). For BP and HR primary or secondary outcomes, there was no evidence of differences in data transmission for notifications sent on weekend versus weekday or morning versus evening. CONCLUSIONS Personalized notifications increased longitudinal adherence to BP and HR transmission from mobile and digital devices among eFHS participants. Our results suggest that personalized messaging is a powerful tool to promote adherence to mobile health systems in cardiovascular research. TRIAL REGISTRATION ClinicalTrials.gov NCT03516019; https://clinicaltrials.gov/ct2/show/NCT03516019.
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Affiliation(s)
- Ludovic Trinquart
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
- Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, United States
- Tufts Clinical and Translational Science Institute, Tufts University, Boston, MA, United States
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
- Framingham Heart Study, Boston University and National Heart, Lung, and Blood Institute, Framingham, MA, United States
| | - David D McManus
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States
- Cardiology Division, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States
- Department of Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | | | - Honghuang Lin
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | - Nicole L Spartano
- Framingham Heart Study, Boston University and National Heart, Lung, and Blood Institute, Framingham, MA, United States
- Section of Endocrinology, Diabetes, Nutrition, and Weight Management, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
| | - Belinda Borrelli
- Center for Behavioral Science Research, Department of Health Policy and Health Services Research, Henry M Goldman School of Dental Medicine, Boston University, Boston, MA, United States
| | - Emelia J Benjamin
- Framingham Heart Study, Boston University and National Heart, Lung, and Blood Institute, Framingham, MA, United States
- Section of Cardiovascular Medicine, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston Medical Center, Boston, MA, United States
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States
| | - Joanne M Murabito
- Framingham Heart Study, Boston University and National Heart, Lung, and Blood Institute, Framingham, MA, United States
- Section of General Internal Medicine, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston Medical Center, Framingham, MA, United States
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7
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Paluch AE, Bajpai S, Ballin M, Bassett DR, Buford TW, Carnethon MR, Chernofsky A, Dooley EE, Ekelund U, Evenson KR, Galuska DA, Jefferis BJ, Kong L, Kraus WE, Larson MG, Lee IM, Matthews CE, Newton RL, Nordström A, Nordström P, Palta P, Patel AV, Pettee Gabriel K, Pieper CF, Pompeii L, Rees-Punia E, Spartano NL, Vasan RS, Whincup PH, Yang S, Fulton JE. Prospective Association of Daily Steps With Cardiovascular Disease: A Harmonized Meta-Analysis. Circulation 2023; 147:122-131. [PMID: 36537288 PMCID: PMC9839547 DOI: 10.1161/circulationaha.122.061288] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 10/20/2022] [Indexed: 12/24/2022]
Abstract
BACKGROUND Taking fewer than the widely promoted "10 000 steps per day" has recently been associated with lower risk of all-cause mortality. The relationship of steps and cardiovascular disease (CVD) risk remains poorly described. A meta-analysis examining the dose-response relationship between steps per day and CVD can help inform clinical and public health guidelines. METHODS Eight prospective studies (20 152 adults [ie, ≥18 years of age]) were included with device-measured steps and participants followed for CVD events. Studies quantified steps per day and CVD events were defined as fatal and nonfatal coronary heart disease, stroke, and heart failure. Cox proportional hazards regression analyses were completed using study-specific quartiles and hazard ratios (HR) and 95% CI were meta-analyzed with inverse-variance-weighted random effects models. RESULTS The mean age of participants was 63.2±12.4 years and 52% were women. The mean follow-up was 6.2 years (123 209 person-years), with a total of 1523 CVD events (12.4 per 1000 participant-years) reported. There was a significant difference in the association of steps per day and CVD between older (ie, ≥60 years of age) and younger adults (ie, <60 years of age). For older adults, the HR for quartile 2 was 0.80 (95% CI, 0.69 to 0.93), 0.62 for quartile 3 (95% CI, 0.52 to 0.74), and 0.51 for quartile 4 (95% CI, 0.41 to 0.63) compared with the lowest quartile. For younger adults, the HR for quartile 2 was 0.79 (95% CI, 0.46 to 1.35), 0.90 for quartile 3 (95% CI, 0.64 to 1.25), and 0.95 for quartile 4 (95% CI, 0.61 to 1.48) compared with the lowest quartile. Restricted cubic splines demonstrated a nonlinear association whereby more steps were associated with decreased risk of CVD among older adults. CONCLUSIONS For older adults, taking more daily steps was associated with a progressively decreased risk of CVD. Monitoring and promoting steps per day is a simple metric for clinician-patient communication and population health to reduce the risk of CVD.
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Affiliation(s)
- Amanda E Paluch
- Department of Kinesiology, Institute for Applied Life Sciences, University of Massachusetts Amherst (A.E.P., S.B., L.K.)
| | - Shivangi Bajpai
- Department of Kinesiology, Institute for Applied Life Sciences, University of Massachusetts Amherst (A.E.P., S.B., L.K.)
| | - Marcel Ballin
- Departments of Community Medicine and Rehabilitation, Unit of Geriatric Medicine (M.B., A.N., P.N.), Umeå University, Sweden
| | - David R Bassett
- Department of Kinesiology, Recreation, and Sport Studies, University of Tennessee, Knoxville (D.R.B.), University of Alabama at Birmingham
| | - Thomas W Buford
- Departments of Medicine, Division of Gerontology/Geriatrics/Palliative Care (T.W.B.), University of Alabama at Birmingham
- Birmingham/Atlanta Geriatric Research, Education, and Clinical Center, Birmingham VA Medical Center, AL (T.W.B.)
| | - Mercedes R Carnethon
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (M.R.C.)
| | - Ariel Chernofsky
- Department of Biostatistics, Boston University, MA (A.C., M.G.L.)
| | - Erin E Dooley
- Epidemiology (E.E.D.' K.P.G.), University of Alabama at Birmingham
| | - Ulf Ekelund
- Department of Sport Medicine, Norwegian School of Sport Sciences, Oslo (U.E.)
- Department of Chronic Diseases and Ageing, Norwegian Institute of Public Health, Oslo (U.E.)
| | - Kelly R Evenson
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina Chapel Hill (K.R.E.)
| | - Deborah A Galuska
- Division of Nutrition, Physical Activity, and Obesity, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA (D.A.G., J.E.F.)
| | - Barbara J Jefferis
- Department of Primary Care and Population Health, University College London Medical School, London, United Kingdom (B.J.J.)
| | - Lingsong Kong
- Department of Kinesiology, Institute for Applied Life Sciences, University of Massachusetts Amherst (A.E.P., S.B., L.K.)
| | - William E Kraus
- Duke Molecular Physiology Institute, Durham, NC (W.E.K.)
- Department of Medicine, Duke University, Durham, NC (W.E.K., C.F.P.)
| | - Martin G Larson
- Department of Biostatistics, Boston University, MA (A.C., M.G.L.)
| | - I-Min Lee
- Brigham and Women's Hospital, Harvard Medical School and Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA (I-M.L.)
| | - Charles E Matthews
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD (C.E.M.)
| | - Robert L Newton
- Pennington Biomedical Research Center, Baton Rouge, LA (R.L.N., S.Y.)
| | - Anna Nordström
- Departments of Community Medicine and Rehabilitation, Unit of Geriatric Medicine (M.B., A.N., P.N.), Umeå University, Sweden
- Public Health and Clinical Medicine, Section of Sustainable Health (A.N.), Umeå University, Sweden
- School of Sport Sciences, UiT The Arctic University of Norway, Tromsø (A.N.)
| | - Peter Nordström
- Departments of Community Medicine and Rehabilitation, Unit of Geriatric Medicine (M.B., A.N., P.N.), Umeå University, Sweden
| | - Priya Palta
- Department of Medicine, Columbia University, New York (P.P.)
| | - Alpa V Patel
- American Cancer Society, Population Science Department, Atlanta, GA (A.V.P., E.R-P.)
| | | | - Carl F Pieper
- Department of Medicine, Duke University, Durham, NC (W.E.K., C.F.P.)
| | - Lisa Pompeii
- Department of Pediatrics, Center for Epidemiology and Population Health, Baylor College of Medicine, Houston, TX (L.P.)
| | - Erika Rees-Punia
- American Cancer Society, Population Science Department, Atlanta, GA (A.V.P., E.R-P.)
| | - Nicole L Spartano
- Departments of Endocrinology, Diabetes, Nutrition and Weight Management (N.L.S.), Boston University School of Medicine, MA
| | - Ramachandran S Vasan
- Medicine and Epidemiology (R.S.V.), Boston University School of Medicine, MA
- Department of Medicine and Epidemiology, Boston University School of Public Health, MA (R.S.V.)
| | - Peter H Whincup
- Population Health Research Institute, St George's' University of London, United Kingdom (P.H.W.)
| | - Shengping Yang
- Pennington Biomedical Research Center, Baton Rouge, LA (R.L.N., S.Y.)
| | - Janet E Fulton
- Division of Nutrition, Physical Activity, and Obesity, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA (D.A.G., J.E.F.)
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Spartano NL, Wang R, Yang Q, Chernofsky A, Murabito JM, Levy D, Vasan RS, DeCarli C, Maillard P, Seshadri S, Beiser AS. Association of Physical Inactivity with MRI Markers of Brain Aging: Assessing Mediation by Cardiometabolic and Epigenetic Factors. J Alzheimers Dis 2023; 95:561-572. [PMID: 37574733 DOI: 10.3233/jad-230289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
INTRODUCTION Cardiometabolic risk factors and epigenetic patterns, increased in physically inactive individuals, are associated with an accelerated brain aging process. OBJECTIVE To determine whether cardiometabolic risk factors and epigenetic patterns mediate the association of physical inactivity with unfavorable brain morphology. METHODS We included dementia and stroke free participants from the Framingham Heart Study Third Generation and Offspring cohorts who had accelerometery and brain MRI data (n = 2,507, 53.9% women, mean age 53.9 years). We examined mediation by the 2017-revised Framingham Stroke Risk Profile (FSRP, using weights for age, cardiovascular disease, atrial fibrillation, diabetes and smoking status, antihypertension medications, and systolic blood pressure) and the homeostatic model of insulin resistance (HOMA-IR) in models of the association of physical inactivity with brain aging, adjusting for age, age-squared, sex, accelerometer wear time, cohort, time from exam-to-MRI, and season. We similarly assessed mediation by an epigenetic age-prediction algorithm, GrimAge, in a smaller sample of participants who had DNA methylation data (n = 1,418). RESULTS FSRP and HOMA-IR explained 8.3-20.5% of associations of higher moderate-to-vigorous physical activity (MVPA), higher steps, and lower sedentary time with higher brain volume. Additionally, FSRP and GrimAge explained 10.3-22.0% of associations of physical inactivity with lower white matter diffusivity and FSRP explained 19.7% of the association of MVPA with lower free water accumulation. CONCLUSION Our results suggest that cardiometabolic risk factors and epigenetic patterns partially mediate the associations of physical inactivity with lower brain volume, higher white matter diffusivity, and aggregation of free water in the extracellular compartments of the brain.
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Affiliation(s)
- Nicole L Spartano
- Section of Endocrinology, Diabetes, Nutrition, and Weight Management, Boston University Chobanian & Avedisian School of Medicine (BUCASM), Boston, MA, USA
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA
| | - Ruiqi Wang
- Department of Biostatistics, Boston University School of Public Health (BUSPH), Boston, MA, USA
| | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health (BUSPH), Boston, MA, USA
| | - Ariel Chernofsky
- Department of Biostatistics, Boston University School of Public Health (BUSPH), Boston, MA, USA
| | - Joanne M Murabito
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA
- Section of General Internal Medicine, Department of Medicine, BUCASM, Boston, MA, USA
| | - Daniel Levy
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ramachandran S Vasan
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA
- Section of Preventive Medicine and Epidemiology, Evans Department of Medicine, BUSM, Boston, MA, USA
- Department of Epidemiology, BUSPH, Boston, MA, USA
- UT School of Public Health in San Antonio, TX, and UT Health Sciences Center in San Antonio, TX, USA
| | - Charles DeCarli
- Department of Neurology University of California Davis, Davis, CA, USA
| | - Pauline Maillard
- Department of Neurology University of California Davis, Davis, CA, USA
| | - Sudha Seshadri
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, BUSM, Boston, MA, USA
- Department of Population Health Sciences, University of Texas Health Science Center, San Antonio, TX, USA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Alexa S Beiser
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health (BUSPH), Boston, MA, USA
- Department of Neurology, BUSM, Boston, MA, USA
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Walker ME, Spartano NL. Identifying Ultra-processed Foods in Nutrition Research: What a Proccess! Neurology 2022; 99:411-412. [PMID: 36219799 DOI: 10.1212/wnl.0000000000201016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 06/10/2022] [Indexed: 11/15/2022] Open
Affiliation(s)
- Maura E Walker
- From the Department of Health Sciences Sargent College of Health and Rehabilitation Sciences, Boston University, Boston, MA and Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Boston, MA (M.E.W.)and Section of Endocrinology, Diabetes, Nutrition and Weight Management, Department of Medicine, Boston University School of Medicine, Boston, MA (N.L.S.)
| | - Nicole L Spartano
- From the Department of Health Sciences Sargent College of Health and Rehabilitation Sciences, Boston University, Boston, MA and Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Boston, MA (M.E.W.)and Section of Endocrinology, Diabetes, Nutrition and Weight Management, Department of Medicine, Boston University School of Medicine, Boston, MA (N.L.S.)
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Tarp J, Fagerland MW, Dalene KE, Johannessen JS, Hansen BH, Jefferis BJ, Whincup PH, Diaz KM, Hooker S, Howard VJ, Chernofsky A, Larson MG, Spartano NL, Vasan RS, Dohrn IM, Hagströmer M, Edwardson C, Yates T, Shiroma EJ, Dempsey PC, Wijndaele K, Anderssen SA, Lee IM, Ekelund U. Device-measured physical activity, adiposity and mortality: a harmonised meta-analysis of eight prospective cohort studies. Br J Sports Med 2022; 56:725-732. [PMID: 34876405 PMCID: PMC9209690 DOI: 10.1136/bjsports-2021-104827] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/17/2021] [Indexed: 12/27/2022]
Abstract
BACKGROUND The joint associations of total and intensity-specific physical activity with obesity in relation to all-cause mortality risk are unclear. METHODS We included 34 492 adults (72% women, median age 62.1 years, 2034 deaths during follow-up) in a harmonised meta-analysis of eight population-based prospective cohort studies with mean follow-up ranging from 6.0 to 14.5 years. Standard body mass index categories were cross-classified with sample tertiles of device-measured total, light-to-vigorous and moderate-to-vigorous physical activity and sedentary time. In five cohorts with waist circumference available, high and low waist circumference was combined with tertiles of moderate-to-vigorous physical activity. RESULTS There was an inverse dose-response relationship between higher levels of total and intensity-specific physical activity and mortality risk in those who were normal weight and overweight. In individuals with obesity, the inverse dose-response relationship was only observed for total physical activity. Similarly, lower levels of sedentary time were associated with lower mortality risk in normal weight and overweight individuals but there was no association between sedentary time and risk of mortality in those who were obese. Compared with the obese-low total physical activity reference, the HRs were 0.59 (95% CI 0.44 to 0.79) for normal weight-high total activity and 0.67 (95% CI 0.48 to 0.94) for obese-high total activity. In contrast, normal weight-low total physical activity was associated with a higher risk of mortality compared with the obese-low total physical activity reference (1.28; 95% CI 0.99 to 1.67). CONCLUSIONS Higher levels of physical activity were associated with lower risk of mortality irrespective of weight status. Compared with obesity-low physical activity, there was no survival benefit of being normal weight if physical activity levels were low.
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Affiliation(s)
- Jakob Tarp
- Department of Sports Medicine, Norwegian School of Sports Sciences, Oslo, Norway
| | - Morten W Fagerland
- Department of Sports Medicine, Norwegian School of Sports Sciences, Oslo, Norway
| | - Knut Eirik Dalene
- Department of Sports Medicine, Norwegian School of Sports Sciences, Oslo, Norway
| | | | - Bjørge H Hansen
- Department of Sports Medicine, Norwegian School of Sports Sciences, Oslo, Norway
- Department of Sport Science and Physical Education, University of Agder, Kristiansand, Norway
| | - Barbara J Jefferis
- Primary Care and Population Health, University College London, London, UK
| | - Peter H Whincup
- Population Health Research Institute, St George's University of London, London, UK
| | - Keith M Diaz
- Department of Medicine, Center for Behavioral Cardiovascular Health, Columbia University Medical Center, New York, New York, USA
| | - Steven Hooker
- College of Health and Human Services, San Diego State University, San Diego, California, USA
| | - Virginia J Howard
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Ariel Chernofsky
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Martin G Larson
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Nicole L Spartano
- Department of Endocrinology, Diabetes, Nutrition and Weight Management, Boston University School of Medicine, Boston, Massachusetts, USA
| | - Ramachandran S Vasan
- Departments of Medicine and Epidemiology, Boston University School of Medicine and Boston University School of Public Health, Boston, Massachusetts, USA
| | - Ing-Mari Dohrn
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Maria Hagströmer
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Academic Primary Health Care Centre, Region Stockholm, Stockholm, Sweden
| | - Charlotte Edwardson
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Thomas Yates
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Eric J Shiroma
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, Maryland, USA
| | - Paddy C Dempsey
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
- Physical Activity and Behavioural Epidemiology Laboratories, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | | | - Sigmund A Anderssen
- Department of Sports Medicine, Norwegian School of Sports Sciences, Oslo, Norway
| | - I-Min Lee
- Department of Epidemiology, Harvard T H Chan School of Public Health, Boston, Massachusetts, USA
- Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Ulf Ekelund
- Department of Sports Medicine, Norwegian School of Sports Sciences, Oslo, Norway
- Department of Chronic Diseases and Ageing, Norwegian Institute of Public Health, Oslo, Norway
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Nayor M, Chernofsky A, Miller PE, Spartano NL, Murthy VL, Malhotra R, Houstis NE, Murabito JM, Clish CB, Larson MG, Vasan RS, Shah RV, Lewis GD. Integrative Analysis of Circulating Metabolite Levels That Correlate With Physical Activity and Cardiorespiratory Fitness. Circ Genom Precis Med 2022; 15:e003592. [PMID: 35536222 PMCID: PMC9233103 DOI: 10.1161/circgen.121.003592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Affiliation(s)
- Matthew Nayor
- Sections of Cardiovascular Medicine & Preventive Medicine and Epidemiology, Dept of Medicine, Boston Univ School of Medicine
| | - Ariel Chernofsky
- Dept of Biostatistics, Boston Univ School of Public Health, Boston, MA
| | | | - Nicole L. Spartano
- Section of Endocrinology, Diabetes, Nutrition & Weight Management, Dept of Medicine, Boston Univ School of Medicine
| | - Venkatesh L. Murthy
- Division of Cardiovascular Medicine, Dept of Medicine, Univ of Michigan, Ann Arbor, MI
- Frankel Cardiovascular Center, Univ of Michigan, Ann Arbor, MI
| | - Rajeev Malhotra
- Cardiology Division, Dept of Medicine, Massachusetts General Hospital, Harvard Medical School
- Cardiovascular Research Center, Massachusetts General Hospital, Boston
| | - Nicholas E. Houstis
- Cardiology Division, Dept of Medicine, Massachusetts General Hospital, Harvard Medical School
| | - Joanne M. Murabito
- Section of General Internal Medicine, Dept of Medicine, Boston Univ School of Medicine
- Boston University’s & National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham
| | | | - Martin G. Larson
- Dept of Biostatistics, Boston Univ School of Public Health, Boston, MA
- Boston University’s & National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham
| | - Ramachandran S. Vasan
- Boston University’s & National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham
- Sections of Preventive Medicine & Epidemiology, and Cardiovascular Medicine, Dept of Medicine, Dept of Epidemiology, Boston Univ Schools of Medicine & Public Health & Center for Computing & Data Sciences, Boston Univ, Boston, MA
| | - Ravi V. Shah
- Cardiology Division, Dept of Medicine, Massachusetts General Hospital, Harvard Medical School
- Vanderbilt Clinical & Translational Research Center, Cardiology Division, Vanderbilt Univ Medical Center, Nashville, TN
| | - Gregory D. Lewis
- Cardiology Division, Dept of Medicine, Massachusetts General Hospital, Harvard Medical School
- Cardiovascular Research Center, Massachusetts General Hospital, Boston
- Pulmonary Critical Care Unit, Massachusetts General Hospital, Boston
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12
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Almohamad M, Krall Kaye E, Mofleh D, Spartano NL. The association of sedentary behaviour and physical activity with periodontal disease in NHANES 2011-2012. J Clin Periodontol 2022; 49:758-767. [PMID: 35634657 DOI: 10.1111/jcpe.13669] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Revised: 04/20/2022] [Accepted: 05/18/2022] [Indexed: 12/30/2022]
Abstract
AIM Periodontal disease is one of the most prevalent oral pathologies and a major chronic disease worldwide. Lifestyle habits such as poor nutrition and smoking have been established to contribute to the development of periodontal disease, but limited research has investigated whether physical activity and sedentary lifestyle play a role. The purpose of this study is to evaluate the association between physical activity, sedentary behaviour, and periodontal disease. MATERIALS AND METHODS We used a nationally representative data set from the National Health and Nutrition Examination Survey (NHANES) 2011-2012. We examined the association between physical activity and sedentary behaviour and periodontal disease using multivariable logistic regression models and reported odds ratios (ORs). RESULTS Individuals with higher total physical activity, higher leisure time physical activity, and lower amount of total sedentary behaviour had lower periodontal disease prevalence. Adjusted multivariable regression models showed that higher sedentary behaviour (more than 7.5 h/day) was associated with higher odds of periodontal disease (OR = 1.17; 95% confidence interval = 1.00-1.36; p = .045). CONCLUSIONS The findings showed that higher sedentary behaviour is associated with higher odds of periodontal disease. Future prospective longitudinal studies and strategies are needed to investigate implications further and define the magnitude of the association between physical activity and periodontal disease.
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Affiliation(s)
- Maha Almohamad
- Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center School of Public Health, Houston, Texas, USA
| | - Elizabeth Krall Kaye
- Health Policy and Health Services Research, Boston University Henry M. Goldman School of Dental Medicine, Boston, Massachusetts, USA
| | - Dania Mofleh
- Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center School of Public Health, Houston, Texas, USA
| | - Nicole L Spartano
- Section of Endocrinology, Diabetes, Nutrition, and Weight Management, Boston University School of Medicine, Boston, Massachusetts, USA
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13
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Kaplan RC, Song RJ, Lin J, Xanthakis V, Hua S, Chernofsky A, Evenson KR, Walker ME, Cuthbertson C, Murabito JM, Cordero C, Daviglus M, Perreira KM, Gellman M, Sotres-Alvarez D, Vasan RS, Xue X, Spartano NL, Mossavar-Rahmani Y. Predictors of incident diabetes in two populations: framingham heart study and hispanic community health study / study of latinos. BMC Public Health 2022; 22:1053. [PMID: 35619100 PMCID: PMC9137165 DOI: 10.1186/s12889-022-13463-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 05/12/2022] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND Non-genetic factors contribute to differences in diabetes risk across race/ethnic and socioeconomic groups, which raises the question of whether effects of predictors of diabetes are similar across populations. We studied diabetes incidence in the primarily non-Hispanic White Framingham Heart Study (FHS, N = 4066) and the urban, largely immigrant Hispanic Community Health Study/Study of Latinos (HCHS/SOL, N = 6891) Please check if the affiliations are captured and presented correctly. METHODS Clinical, behavioral, and socioeconomic characteristics were collected at in-person examinations followed by seven-day accelerometry. Among individuals without diabetes, Cox proportional hazards regression models (both age- and sex-adjusted, and then multivariable-adjusted for all candidate predictors) identified predictors of incident diabetes over a decade of follow-up, defined using clinical history or laboratory assessments. RESULTS Four independent predictors were shared between FHS and HCHS/SOL. In each cohort, the multivariable-adjusted hazard of diabetes increased by approximately 50% for every ten-year increment of age and every five-unit increment of body mass index (BMI), and was 50-70% higher among hypertensive than among non-hypertensive individuals (all P < 0.01). Compared with full-time employment status, the multivariable-adjusted hazard ratio (HR) and 95% confidence interval (CI) for part-time employment was 0.61 (0.37,1.00) in FHS and 0.62 (0.41,0.95) in HCHS/SOL. Moderate-to-vigorous physical activity (MVPA) was an additional predictor in common observed in age- and sex-adjusted models, which did not persist after adjustment for other covariates (compared with MVPA ≤ 5 min/day, HR for MVPA level ≥ 30 min/day was 0.48 [0.31,0.74] in FHS and 0.74 [0.56,0.97] in HCHS/SOL). Additional predictors found in sex- and age-adjusted analyses among the FHS participants included male gender and lower education, but these predictors were not found to be independent of others in multivariable adjusted models, nor were they associated with diabetes risk among HCHS/SOL adults. CONCLUSIONS The same four independent predictors - age, body mass index, hypertension and employment status - were associated with diabetes risk across two disparate US populations. While the reason for elevated diabetes risk in full-time workers is unclear, the findings suggest that diabetes may be part of the work-related burden of disease. Our findings also support prior evidence that differences by gender and socioeconomic position in diabetes risk are not universally present across populations.
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Affiliation(s)
- Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, 1300 Morris Park Avenue. Belfer building, Room 1315, Bronx, NY, 10461, USA.
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
| | - Rebecca J Song
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Juan Lin
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, 1300 Morris Park Avenue. Belfer building, Room 1315, Bronx, NY, 10461, USA
| | - Vanessa Xanthakis
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Simin Hua
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, 1300 Morris Park Avenue. Belfer building, Room 1315, Bronx, NY, 10461, USA
| | | | - Kelly R Evenson
- Department of Epidemiology Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Maura E Walker
- Department of Health Sciences, Boston University College of Health & Rehabilitation Sciences, Boston, MA, USA
| | - Carmen Cuthbertson
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Joanne M Murabito
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Christina Cordero
- Department of Psychology, Don Soffer Clinical Research Center, University of Miami, Miami, FL, USA
| | - Martha Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA
| | - Krista M Perreira
- Department of Social Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Marc Gellman
- Department of Psychology, University of Miami, Miami, FL, USA
| | - Daniela Sotres-Alvarez
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | | | - Xiaonan Xue
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, 1300 Morris Park Avenue. Belfer building, Room 1315, Bronx, NY, 10461, USA
| | - Nicole L Spartano
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Yasmin Mossavar-Rahmani
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, 1300 Morris Park Avenue. Belfer building, Room 1315, Bronx, NY, 10461, USA
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14
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Zhang 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; 7:e29107. [PMID: 34994694 PMCID: PMC8783285 DOI: 10.2196/29107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 07/10/2021] [Accepted: 11/24/2021] [Indexed: 11/13/2022] Open
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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Affiliation(s)
- Yuankai Zhang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | | | - Michael M Hammond
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States
| | - Hongshan Liu
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States
| | - Honghuang Lin
- Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, United States
| | - Mayank Sardana
- Cardiology Division, Department of Medicine, University of California San Francisco, San Francisco, CA, United States
| | - Ludovic Trinquart
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Belinda Borrelli
- Center for Behavioral Science Research, Henry M. Goldman School of Dental Medicine, Boston University, Boston, MA, United States
| | - Emily S Manders
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States
| | - Jelena Kornej
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States
| | - Nicole L Spartano
- Section of Endocrinology, Diabetes, Nutrition, and Weight Management, Boston University School of Medicine, Boston, MA, United States
| | | | | | - Emelia J Benjamin
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States.,Section of Preventive Medicine and Epidemiology and Cardiovascular Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, United States.,Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States
| | - David D McManus
- Cardiology Division, Department of Medicine, University of Massachusetts Medical School, Worcester, MA, United States.,Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, United States
| | - Joanne M Murabito
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States.,Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, United States
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
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15
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Trethewey RE, Spartano NL, Vasan RS, Larson MG, O’Connor GT, Esliger DW, Petherick ES, Steiner MC. Body mass index across adulthood and the development of airflow obstruction and emphysema. Chron Respir Dis 2022; 19:14799731221139294. [DOI: 10.1177/14799731221139294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
Background Low body mass index (BMI) is associated with COPD, but temporal relationships between airflow obstruction (AO) development and emphysematous change are unclear. We investigated longitudinal changes in BMI, AO, and lung density throughout adulthood using data from the Framingham Offspring Cohort (FOC). Methods BMI trajectories were modelled throughout adulthood in 4587 FOC participants from Exam 2 (mean age = 44), through Exam 9 (mean age = 71), in AO participants and non-AO participants (AO n = 1036), determined by spirometry, using fractional polynomial growth curves. This process was repeated for low lung density (LLD) and non LLD participants (LLD n = 225) determined by Computed Tomography. Spirometry decline was compared separately between tertiles of BMI in those aged <40 years and associations between fat and lean mass (measured using Dual Energy X-ray Absorptiometry, DEXA) and development of AO and LLD were also assessed. Additional analyses were performed with adjustment for smoking volume. Results The BMI trajectory from 30 years of age was visually lower in the AO group than both non-AO smokers (non-<AO-S) and non-AO non-smokers (non-AO-N). Similarly, BMI trajectories were visually lower in participants with LLD throughout adulthood compared to normal lung density smokers and non-smokers. Differences remained after adjustment for smoking volume. The lowest BMI tertile in ages <40 years was associated with the steepest subsequent decline in FEV1/FVC ratio in both sexes. Conclusion Mean BMI is lower throughout adulthood in AO and LLD participants. Lower BMI is associated with a steeper decline in the ratio of FEV1/FVC. These findings suggest body mass may precede and potentially have a role in the development of COPD lung pathophysiology.
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Affiliation(s)
- Ruth E Trethewey
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
- National Centre for Sport and Exercise Medicine, Loughborough University, Loughborough, UK
| | - Nicole L Spartano
- Lung and Blood Institute’s Framingham Heart Study, Boston University and National Heart, Framingham, MA, USA
| | - Ramachandran S Vasan
- Lung and Blood Institute’s Framingham Heart Study, Boston University and National Heart, Framingham, MA, USA
| | - Martin G Larson
- Lung and Blood Institute’s Framingham Heart Study, Boston University and National Heart, Framingham, MA, USA
| | - George T O’Connor
- Lung and Blood Institute’s Framingham Heart Study, Boston University and National Heart, Framingham, MA, USA
| | - Dale W Esliger
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
- National Centre for Sport and Exercise Medicine, Loughborough University, Loughborough, UK
| | - Emily S Petherick
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
- National Centre for Sport and Exercise Medicine, Loughborough University, Loughborough, UK
| | - Michael C Steiner
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
- National Centre for Sport and Exercise Medicine, Loughborough University, Loughborough, UK
- Centre for Exercise and Rehabilitation Services, Leicester, UK
- NIHR Leicester Biomedical Research Centre––Respiratory, University of Leicester, Leicester, UK
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16
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Spartano NL, Himali JJ, Trinquart L, Yang Q, Weinstein G, Satizabal CL, Dukes KA, Beiser AS, Murabito JM, Vasan RS, Seshadri S. Accelerometer-Measured, Habitual Physical Activity and Circulating Brain-Derived Neurotrophic Factor: A Cross-Sectional Study. J Alzheimers Dis 2021; 85:805-814. [PMID: 34864673 DOI: 10.3233/jad-215109] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
BACKGROUND One of the mechanisms suggested to link physical activity (PA) to favorable brain health is through stimulation of neural growth factors such as brain-derived neurotrophic factor (BDNF). Acute bouts of PA stimulate circulating BDNF levels. OBJECTIVE In this investigation, we assessed whether habitual, accelerometer-measured PA levels were related to circulating BDNF levels in a middle-aged cohort. METHODS In the Framingham Heart Study Third Generation cohort, 1,769 participants provided reliable accelerometry data and were not missing BDNF measurement and platelet counts. In a cross-sectional analysis, using multivariable regression, we related PA measures to serum BDNF levels, adjusting for age, sex, smoking status, platelet count, depression status, and accelerometer wear time. RESULTS Our study participants (mean age 47±9 years, 50.8% women) spent an average of 22.3 mins/day moderate-to-vigorous (MV)PA. Most PA variables (steps, MVPA, light activity, and sedentary time) were not related to BDNF levels (p > 0.05). We observed a non-linear trend, where 15-50 mins/week vigorous activity was associated with lower BDNF compared to those with 0 min vigorous activity (β= -0.049±0.024, p = 0.05), but with no significant associations at lower or higher vigorous activity levels. In smokers, MVPA was also associated with lower BDNF levels (β= -0.216±0.079, p = 0.01). CONCLUSION Our study reveals that circulating BDNF is not chronically elevated in individuals with higher levels of habitual PA in middle-aged adults from the community and may even be chronically suppressed with higher PA in subgroups, including current smokers. These results do not contradict previous studies demonstrating that circulating BDNF rises acutely after PA.
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Affiliation(s)
- Nicole L Spartano
- Section of Endocrinology, Diabetes, Nutrition, and Weight Management, Boston University School of Medicine (BUSM), Boston, MA, USA.,Framingham Heart Study, Framingham, MA, USA
| | - Jayandra J Himali
- Framingham Heart Study, Framingham, MA, USA.,Department of Biostatistics, Boston University School of Public Health (BUSPH), Boston, MA, USA.,Department of Neurology, BUSM, Boston, MA, USA.,Department of Population Health Sciences, University of Texas Health Science Center, San Antonio, TX, USA.,Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, San Antonio, TX, USA
| | - Ludovic Trinquart
- Department of Biostatistics, Boston University School of Public Health (BUSPH), Boston, MA, USA
| | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health (BUSPH), Boston, MA, USA
| | | | - Claudia L Satizabal
- Framingham Heart Study, Framingham, MA, USA.,Department of Neurology, BUSM, Boston, MA, USA.,Department of Population Health Sciences, University of Texas Health Science Center, San Antonio, TX, USA.,Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, San Antonio, TX, USA
| | - Kimberly A Dukes
- Department of Biostatistics, Boston University School of Public Health (BUSPH), Boston, MA, USA.,Biostatistics and Epidemiology Data Analysis Center, BUSPH, Boston, MA USA
| | - Alexa S Beiser
- Framingham Heart Study, Framingham, MA, USA.,Department of Biostatistics, Boston University School of Public Health (BUSPH), Boston, MA, USA.,Department of Neurology, BUSM, Boston, MA, USA
| | - Joanne M Murabito
- Framingham Heart Study, Framingham, MA, USA.,Departments of Medicine and Epidemiology, BUSM and BUSPH, Boston, MA, USA
| | - Ramachandran S Vasan
- Framingham Heart Study, Framingham, MA, USA.,Departments of Medicine and Epidemiology, BUSM and BUSPH, Boston, MA, USA
| | - Sudha Seshadri
- Framingham Heart Study, Framingham, MA, USA.,Department of Neurology, BUSM, Boston, MA, USA.,Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, San Antonio, TX, USA
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17
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Nayor M, Chernofsky A, Spartano NL, Tanguay M, Blodgett JB, Murthy VL, Malhotra R, Houstis NE, Velagaleti RS, Murabito JM, Larson MG, Vasan RS, Shah RV, Lewis GD. Physical activity and fitness in the community: the Framingham Heart Study. Eur Heart J 2021; 42:4565-4575. [PMID: 34436560 PMCID: PMC8633734 DOI: 10.1093/eurheartj/ehab580] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 06/14/2021] [Accepted: 08/10/2021] [Indexed: 12/21/2022] Open
Abstract
AIMS While greater physical activity (PA) is associated with improved health outcomes, the direct links between distinct components of PA, their changes over time, and cardiorespiratory fitness are incompletely understood. METHODS AND RESULTS Maximum effort cardiopulmonary exercise testing (CPET) and objective PA measures [sedentary time (SED), steps/day, and moderate-vigorous PA (MVPA)] via accelerometers worn for 1 week concurrent with CPET and 7.8 years prior were obtained in 2070 Framingham Heart Study participants [age 54 ± 9 years, 51% women, SED 810 ± 83 min/day, steps/day 7737 ± 3520, MVPA 22.3 ± 20.3 min/day, peak oxygen uptake (VO2) 23.6 ± 6.9 mL/kg/min]. Adjusted for clinical risk factors, increases in steps/day and MVPA and reduced SED between the two assessments were associated with distinct aspects of cardiorespiratory fitness (measured by VO2) during initiation, early-moderate level, peak exercise, and recovery, with the highest effect estimates for MVPA (false discovery rate <5% for all). Findings were largely consistent across categories of age, sex, obesity, and cardiovascular risk. Increases of 17 min of MVPA/day [95% confidence interval (CI) 14-21] or 4312 steps/day (95% CI 3439-5781; ≈54 min at 80 steps/min), or reductions of 249 min of SED per day (95% CI 149-777) between the two exam cycles corresponded to a 5% (1.2 mL/kg/min) higher peak VO2. Individuals with high (above-mean) steps or MVPA demonstrated above average peak VO2 values regardless of whether they had high or low SED. CONCLUSIONS Our findings provide a detailed assessment of relations of different types of PA with multidimensional cardiorespiratory fitness measures and suggest favourable longitudinal changes in PA (and MVPA in particular) are associated with greater objective fitness.
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Affiliation(s)
- Matthew Nayor
- Sections of Cardiology and Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, 72 E Concord St, Suite L-514, Boston, MA 02118, USA
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Ariel Chernofsky
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Nicole L Spartano
- Department of Medicine, Section of Endocrinology, Diabetes, Nutrition and Weight Management, Boston University School of Medicine, Boston, MA, USA
| | - Melissa Tanguay
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Jasmine B Blodgett
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Venkatesh L Murthy
- Division of Cardiovascular Medicine, Department of Medicine, University of Michigan, Ann Arbor, MI, USA
- Frankel Cardiovascular Center, University of Michigan, Ann Arbor, MI, USA
| | - Rajeev Malhotra
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Nicholas E Houstis
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Raghava S Velagaleti
- Cardiology Section, Department of Medicine, Boston VA Healthcare System, West Roxbury, MA, USA
| | - Joanne M Murabito
- Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
- Boston University’s and National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, MA, USA
| | - Martin G Larson
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Boston University’s and National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, MA, USA
| | - Ramachandran S Vasan
- Boston University’s and National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, MA, USA
- Sections of Preventive Medicine and Epidemiology, and Cardiology, Department of Medicine, Department of Epidemiology, Boston University Schools of Medicine and Public Health, Center for Computing and Data Sciences, Boston University, Boston, MA, USA
| | - Ravi V Shah
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Vanderbilt Clinical and Translational Research Center, Cardiology Division, Vanderbilt University Medical Center, Nashville, TN
| | - Gregory D Lewis
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Pulmonary Critical Care Unit, Massachusetts General Hospital, Boston, MA USA
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18
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Affiliation(s)
- Nicole L Spartano
- Section of Endocrinology, Diabetes, Nutrition, and Weight Management, Boston University School of Medicine, Boston, Massachusetts
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19
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Hammond MM, Zhang Y, Pathiravasan CH, Lin H, Sardana M, Trinquart L, Benjamin EJ, Borrelli B, Manders ES, Fusco K, Kornej J, Spartano NL, Kheterpal V, Nowak C, McManus DD, Liu C, Murabito JM. Relations between body mass index trajectories and habitual physical activity measured by smartwatch in the electronic cohort of the Framingham Heart Study: Cohort Study (Preprint). JMIR Cardio 2021; 6:e32348. [PMID: 35476038 PMCID: PMC9096636 DOI: 10.2196/32348] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 01/14/2022] [Accepted: 03/14/2022] [Indexed: 12/11/2022] Open
Abstract
Background Objective Methods Results Conclusions
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Affiliation(s)
- Michael M Hammond
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States
| | - Yuankai Zhang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | | | - Honghuang Lin
- Division of Clinical Informatics, Department of Medicine, University of Massachusetts Medical School, Worcester, MA, United States
| | - Mayank Sardana
- Cardiology Division, Department of Medicine, University of California San Francisco, San Francisco, CA, United States
| | - Ludovic Trinquart
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Emelia J Benjamin
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States
- Section of Cardiovascular Medicine, Department of Medicine, Boston Medical Center and Boston University School of Medicine, Boston, MA, United States
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States
| | - Belinda Borrelli
- Department of Health Policy & Health Services Research, Henry M Goldman School of Dental Medicine, Boston University, Boston, MA, United States
| | - Emily S Manders
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States
| | - Kelsey Fusco
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States
| | - Jelena Kornej
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States
| | - Nicole L Spartano
- Section of Endocrinology, Diabetes, Nutrition, and Weight Management, Boston University School of Medicine, Boston, MA, United States
| | | | | | - David D McManus
- Cardiology Division, Department of Medicine, University of Massachusetts Medical School, Worcester, MA, United States
- Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, United States
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Joanne M Murabito
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States
- Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, United States
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20
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Barone Gibbs B, Hivert MF, Jerome GJ, Kraus WE, Rosenkranz SK, Schorr EN, Spartano NL, Lobelo F. Physical Activity as a Critical Component of First-Line Treatment for Elevated Blood Pressure or Cholesterol: Who, What, and How?: A Scientific Statement From the American Heart Association. Hypertension 2021; 78:e26-e37. [PMID: 34074137 DOI: 10.1161/hyp.0000000000000196] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Current guidelines published by the American Heart Association and the American College of Cardiology broadly recommend lifestyle approaches to prevent and treat elevated blood pressure and cholesterol. For patients with mildly or moderately elevated blood pressure and blood cholesterol, lifestyle-only approaches are the first line of therapy. The purpose of this scientific statement is to: (1) highlight the mild-moderate-risk patient groups indicated for lifestyle-only treatment for elevated blood pressure or cholesterol; (2) describe recommendations, average effects, and additional considerations when prescribing lifestyle treatment with physical activity; and (3) provide guidance and resources for clinicians to assess, prescribe, counsel, and refer to support increased physical activity in their patients. An estimated 21% and 28% to 37% of US adults, respectively, have mild-moderate-risk blood pressure and cholesterol and should receive lifestyle-only as first-line treatment. Of the recommended lifestyle changes, increasing physical activity has extensive benefits, including improving both blood pressure and blood cholesterol, that are comparable, superior, or complementary to other healthy lifestyle changes. Physical activity assessment and prescription are an excellent lifestyle behavior treatment option for all patients, including for the large population of mild-moderate-risk patients with elevated blood pressure and blood cholesterol.
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21
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Lee J, Walker ME, Bourdillon MT, Spartano NL, Rogers GT, Jacques PF, Vasan RS, Xanthakis V. Conjoint Associations of Adherence to Physical Activity and Dietary Guidelines With Cardiometabolic Health: The Framingham Heart Study. J Am Heart Assoc 2021; 10:e019800. [PMID: 33784828 PMCID: PMC8174320 DOI: 10.1161/jaha.120.019800] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Background The conjoint associations of adherence to the recent physical activity and dietary guidelines with the metabolic syndrome (MetS) are incompletely understood. Methods and Results We evaluated 2379 FHS (Framingham Heart Study) Third Generation participants (mean age, 47 years; 54.4% women) attending examination cycle 2. We examined the cross‐sectional relations of adherence to the 2018 Physical Activity Guidelines for Americans (binary; moderate‐to‐vigorous physical activity ≥150 versus <150 min/wk) and 2015 Dietary Guidelines for Americans (binary; 2015 Dietary Guidelines for Americans Adherence Index ≥median versus <median [score, 62.1/100]) with prevalence of the MetS using generalized linear models. We also related adherence to guidelines with the incidence of MetS prospectively, using Cox proportional hazards regression with discrete time intervals. Adherence rates to the 2018 Physical Activity Guidelines for Americans (odds ratio [OR], 0.49; 95% CI, 0.40–0.60) and 2015 Dietary Guidelines for Americans (OR, 0.67; 95% CI, 0.51–0.90) were individually associated with lower odds of prevalent MetS, whereas conjoint adherence to both guidelines was associated with the lowest odds of MetS (OR, 0.35; 95% CI, 0.26–0.47) compared with the referent group (nonadherence to both guidelines). Adherence rates to the 2018 Physical Activity Guidelines for Americans (hazard ratio [HR], 0.66; 95% CI, 0.50–0.88) and 2015 Dietary Guidelines for Americans (HR, 0.68; 95% CI, 0.51–0.90) were associated with lower risk of MetS, prospectively. In addition, we observed a 52% lower risk of MetS in individuals who adhered to both guidelines compared with the referent group. Conclusions Maintaining both regular physical activity and a healthy diet in midlife may be required for optimal cardiometabolic health in later life.
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Affiliation(s)
- Joowon Lee
- Section of Preventive Medicine and Epidemiology Boston University School of Medicine Boston MA
| | - Maura E Walker
- Section of Preventive Medicine and Epidemiology Boston University School of Medicine Boston MA.,Department of Health Sciences Sargent College of Health and Rehabilitation SciencesBoston University Boston MA
| | | | - Nicole L Spartano
- Section of Endocrinology Diabetes, Nutrition, and Weight Management Boston University School of Medicine Boston MA.,FHS (Framingham Heart Study) Framingham MA
| | - Gail T Rogers
- Nutritional Epidemiology Program Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging at Tufts University Boston MA
| | - Paul F Jacques
- Nutritional Epidemiology Program Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging at Tufts University Boston MA
| | - Ramachandran S Vasan
- Section of Preventive Medicine and Epidemiology Boston University School of Medicine Boston MA.,FHS (Framingham Heart Study) Framingham MA.,Department of Epidemiology Boston University School of Public Health Boston MA.,Section of Cardiovascular Medicine Department of Medicine Boston University School of Medicine Boston MA.,Center for Computing and Data Sciences Boston University Boston MA
| | - Vanessa Xanthakis
- Section of Preventive Medicine and Epidemiology Boston University School of Medicine Boston MA.,FHS (Framingham Heart Study) Framingham MA.,Department of Biostatistics Boston University School of Public Health Boston MA
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22
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Pathiravasan CH, Zhang Y, Trinquart L, Benjamin EJ, Borrelli B, McManus DD, Kheterpal V, Lin H, Sardana M, Hammond MM, Spartano NL, Dunn AL, Schramm E, Nowak C, Manders ES, Liu H, Kornej J, Liu C, Murabito JM. Adherence of Mobile App-Based Surveys and Comparison With Traditional Surveys: eCohort Study. J Med Internet Res 2021; 23:e24773. [PMID: 33470944 PMCID: PMC7857942 DOI: 10.2196/24773] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 12/15/2020] [Accepted: 12/19/2020] [Indexed: 01/25/2023] Open
Abstract
Background eCohort studies offer an efficient approach for data collection. However, eCohort studies are challenged by volunteer bias and low adherence. We designed an eCohort embedded in the Framingham Heart Study (eFHS) to address these challenges and to compare the digital data to traditional data collection. Objective The aim of this study was to evaluate adherence of the eFHS app-based surveys deployed at baseline (time of enrollment in the eCohort) and every 3 months up to 1 year, and to compare baseline digital surveys with surveys collected at the research center. Methods We defined adherence rates as the proportion of participants who completed at least one survey at a given 3-month period and computed adherence rates for each 3-month period. To evaluate agreement, we compared several baseline measures obtained in the eFHS app survey to those obtained at the in-person research center exam using the concordance correlation coefficient (CCC). Results Among the 1948 eFHS participants (mean age 53, SD 9 years; 57% women), we found high adherence to baseline surveys (89%) and a decrease in adherence over time (58% at 3 months, 52% at 6 months, 41% at 9 months, and 40% at 12 months). eFHS participants who returned surveys were more likely to be women (adjusted odds ratio [aOR] 1.58, 95% CI 1.18-2.11) and less likely to be smokers (aOR 0.53, 95% CI 0.32-0.90). Compared to in-person exam data, we observed moderate agreement for baseline app-based surveys of the Physical Activity Index (mean difference 2.27, CCC=0.56), and high agreement for average drinks per week (mean difference 0.54, CCC=0.82) and depressive symptoms scores (mean difference 0.03, CCC=0.77). Conclusions We observed that eFHS participants had a high survey return at baseline and each 3-month survey period over the 12 months of follow up. We observed moderate to high agreement between digital and research center measures for several types of surveys, including physical activity, depressive symptoms, and alcohol use. Thus, this digital data collection mechanism is a promising tool to collect data related to cardiovascular disease and its risk factors.
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Affiliation(s)
| | - Yuankai Zhang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Ludovic Trinquart
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Emelia J Benjamin
- Section of Preventive Medicine and Epidemiology and Cardiovascular Medicine, Department of Medicine, and Department of Epidemiology, Boston University Schools of Medicine and Public Health, Boston, MA, United States.,Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States
| | - Belinda Borrelli
- Center for Behavioral Science Research, Department of Health Policy & Health Services Research, Boston University Henry M Goldman School of Dental Medicine, Boston, MA, United States
| | - David D McManus
- Cardiology Division, Department of Medicine, University of Massachusetts Medical School, Worcester, MA, United States.,Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, United States
| | | | - Honghuang Lin
- Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, United States
| | - Mayank Sardana
- Cardiology Division, Department of Medicine, University of California San Francisco, San Francisco, CA, United States
| | - Michael M Hammond
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States
| | - Nicole L Spartano
- Section of Endocrinology, Diabetes, Nutrition, and Weight Management, Boston University School of Medicine, Boston, MA, United States
| | - Amy L Dunn
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States
| | | | | | - Emily S Manders
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States
| | - Hongshan Liu
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States
| | - Jelena Kornej
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Joanne M Murabito
- Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, United States
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23
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Affiliation(s)
- Nicole L Spartano
- From the Section of Endocrinology, Diabetes, Nutrition & Weight Management (N.L.S.), Boston University School of Medicine, MA; and Luigi Sacco Department of Biomedical and Clinical Sciences (L.P.), University of Milan, Italy.
| | - Leonardo Pantoni
- From the Section of Endocrinology, Diabetes, Nutrition & Weight Management (N.L.S.), Boston University School of Medicine, MA; and Luigi Sacco Department of Biomedical and Clinical Sciences (L.P.), University of Milan, Italy
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24
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Chen GC, Qi Q, Hua S, Moon JY, Spartano NL, Vasan RS, Sotres-Alvarez D, Castaneda SF, Evenson KR, Perreira KM, Gallo LC, Pirzada A, Diaz KM, Daviglus ML, Gellman MD, Kaplan RC, Xue X, Mossavar-Rahmani Y. Accelerometer-assessed physical activity and incident diabetes in a population covering the adult life span: the Hispanic Community Health Study/Study of Latinos. Am J Clin Nutr 2020; 112:1318-1327. [PMID: 32910816 PMCID: PMC7657343 DOI: 10.1093/ajcn/nqaa232] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Accepted: 07/23/2020] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND The association between accelerometer-assessed physical activity and risk of diabetes remains unclear, especially among US Hispanic/Latino adults who have lower levels of physical activity and a higher diabetes burden compared with other racial/ethnical populations in the country. OBJECTIVES To examine the association between accelerometer-assessed physical activity and incident diabetes in a US Hispanic/Latino population. METHODS We included 7280 participants of the Hispanic Community Health Study/Study of Latinos who aged 18-74 y and free of diabetes at baseline. Data on moderate-to-vigorous physical activity (MVPA) were collected using a 7-d accelerometer measurement. Incident diabetes was assessed after a mean ± SD of 6.0 ± 0.8 y using standard procedures including blood tests. RRs and 95% CIs of diabetes associated with MVPA were estimated using survey Poisson regressions. The associations of MVPA with 6-y changes in adiposity measures were also examined. RESULTS A total of 871 incident cases of diabetes were identified. MVPA was inversely and nonlinearly associated with risk of diabetes (P-nonlinearity = 0.006), with benefits accruing rapidly at the lower end of MVPA range (<30 min/d) and leveling off thereafter. The association differed by population age (P-interaction = 0.006). Higher MVPA was associated with lower risk of diabetes among individuals older than 50 y (RRQ4 versus Q1 = 0.50; 95% CI: 0.35, 0.73; P-trend < 0.001) but not among younger individuals (RRQ4 versus Q1 = 0.98; 95% CI: 0.66, 1.47; P-trend = 0.92). An inverse association between MVPA and 6-y gain in waist circumference was also limited to the older group (P-interaction with age < 0.001). CONCLUSIONS Among US Hispanic/Latino adults, baseline accelerometer-derived MVPA was inversely associated with incident diabetes only among individuals aged 50 y and older. Further studies are needed to confirm our findings and to clarify potential mechanisms underlying the possible age differences in the MVPA-diabetes association. This study was registered at clinicaltrials.gov as NCT02060344.
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Affiliation(s)
- Guo-Chong Chen
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Qibin Qi
- Address correspondence to QQ (E-mail: )
| | - Simin Hua
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Jee-Young Moon
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Nicole L Spartano
- Sections of Preventative Medicine and Epidemiology, and Cardiology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA,The Whitaker Cardiovascular Institute, Boston University School of Medicine, Boston, MA, USA
| | - Ramachandran S Vasan
- Departments of Medicine and Epidemiology, Boston University Schools of Medicine and Public Health, Boston, MA, USA
| | - Daniela Sotres-Alvarez
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Sheila F Castaneda
- Department of Psychology, San Diego State University, San Diego, CA, USA
| | - Kelly R Evenson
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Krista M Perreira
- Department of Social Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Linda C Gallo
- Department of Psychology, San Diego State University, San Diego, CA, USA
| | - Amber Pirzada
- Institute for Minority Health Research, University of Illinois at Chicago, IL, USA
| | - Keith M Diaz
- Center for Behavioral Cardiovascular Health, Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Martha L Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, IL, USA
| | - Marc D Gellman
- Behavioral Medicine Research Center, Department of Psychology, University of Miami, Miami, FL, USA
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA,Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Xiaonan Xue
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Yasmin Mossavar-Rahmani
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
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Lin H, Sardana M, Zhang Y, Liu C, Trinquart L, Benjamin EJ, Manders ES, Fusco K, Kornej J, Hammond MM, Spartano NL, Pathiravasan CH, Kheterpal V, Nowak C, Borrelli B, Murabito JM, McManus DD. Association of Habitual Physical Activity With Cardiovascular Disease Risk. Circ Res 2020; 127:1253-1260. [PMID: 32842915 DOI: 10.1161/circresaha.120.317578] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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.
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Affiliation(s)
- Honghuang Lin
- Section of Computational Biomedicine, Department of Medicine (H.L.), Boston University School of Medicine, MA
| | - Mayank Sardana
- Cardiology Division, Department of Medicine, University of California San Francisco (M.S.)
| | - Yuankai Zhang
- Department of Biostatistics, Boston University School of Public Health, MA (Y.Z., C.L., L.T., C.H.P.)
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, MA (Y.Z., C.L., L.T., C.H.P.)
| | - Ludovic Trinquart
- Department of Biostatistics, Boston University School of Public Health, MA (Y.Z., C.L., L.T., C.H.P.)
| | - Emelia J Benjamin
- 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.)
- 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.)
| | - Emily S Manders
- 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.)
| | - Kelsey Fusco
- 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.)
| | - Jelena Kornej
- 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.)
| | - Michael M Hammond
- 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.)
| | - Nicole L Spartano
- Section of Endocrinology, Diabetes, Nutrition, and Weight Management (N.L.S.), Boston University School of Medicine, MA
| | | | | | | | - Belinda Borrelli
- Henry M. Goldman School of Dental Medicine, Center for Behavioral Science Research, Department of Health Policy & Health Services Research, Boston University, MA (B.B.)
| | - Joanne M Murabito
- Section of General Internal Medicine, Department of Medicine (J.M.M.), Boston University School of Medicine, MA
- 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.)
| | - David D McManus
- Cardiology Division, Department of Medicine (D.D.M.), University of Massachusetts Medical School, Worcester
- Department of Quantitative Health Sciences (D.D.M.), University of Massachusetts Medical School, Worcester
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Lin HP, Lynk N, Moore LL, Cabral HJ, Heffernan KS, Dumas AK, Hruska B, Zajdel RA, Gump BB, Spartano NL. A pragmatic approach to the comparison of wrist-based cutpoints of physical activity intensity for the MotionWatch8 accelerometer in children. PLoS One 2020; 15:e0234725. [PMID: 32559207 PMCID: PMC7304605 DOI: 10.1371/journal.pone.0234725] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 06/01/2020] [Indexed: 11/24/2022] Open
Abstract
Background A variety of wearable monitors are available for objectively assessing physical activity but there is a lack of established values for the activity intensity of MotionWatch8 (MW8) and a similar lack of studies on comparability across devices. Our study aimed to establish activity intensity cutpoints for the MW8 accelerometer in children, which are necessary to determine whether they are meeting physical activity guidelines. Methods Children (n = 39, ages 9–13 years) were asked to wear two different accelerometers (MW8 and ActiGraph) simultaneously on the same dominant wrist as they performed different activities designed to mimic activities of variable intensity that a child might perform in a free-living environment. Linear regression and receiver operating characteristic (ROC) curves were performed to assess sensitivity and specificity of the identified MW8 intensity cutpoints compared to established ActiGraph cutpoints. Results Mean values for each activity were positively correlated using the MW8 and ActiGraph monitors (r = 0.85, p<0.001). The optimal cutpoints for differentiating sedentary from light physical activity, light from moderate, and moderate from vigorous activity were ≤32 counts, ≥ 371.5 counts, and ≥ 859.5 counts per 30 seconds, respectively. Conclusions Our study demonstrated the ability of MW8 to discriminate different intensity activities and provided the first cutoff values for researchers using the MW8 to measure physical activity patterns among children.
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Affiliation(s)
- Hsuan-Ping Lin
- Department of Medicine/Preventative Medicine and Epidemiology, Boston University School of Medicine, Boston, MA, United States of America
| | - Nicole Lynk
- Department of Public Health, Food Studies, and Nutrition, Syracuse University, Syracuse, NY, United States of America
| | - Lynn L. Moore
- Department of Medicine/Preventative Medicine and Epidemiology, Boston University School of Medicine, Boston, MA, United States of America
| | - Howard J. Cabral
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States of America
| | - Kevin S. Heffernan
- Department of Exercise Science, Syracuse University, Syracuse, NY, United States of America
| | - Amy K. Dumas
- Department of Public Health, Food Studies, and Nutrition, Syracuse University, Syracuse, NY, United States of America
| | - Bryce Hruska
- Department of Public Health, Food Studies, and Nutrition, Syracuse University, Syracuse, NY, United States of America
| | - Rachel A. Zajdel
- Department of Public Health, Food Studies, and Nutrition, Syracuse University, Syracuse, NY, United States of America
| | - Brooks B. Gump
- Department of Public Health, Food Studies, and Nutrition, Syracuse University, Syracuse, NY, United States of America
| | - Nicole L. Spartano
- Section of Endocrinology, Diabetes, Nutrition & Weight Management, Department of Medicine, Boston University School of Medicine, Boston, MA, United States of America
- * E-mail:
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Virani SS, Alonso A, Benjamin EJ, Bittencourt MS, Callaway CW, Carson AP, Chamberlain AM, Chang AR, Cheng S, Delling FN, Djousse L, Elkind MSV, Ferguson JF, Fornage M, Khan SS, Kissela BM, Knutson KL, Kwan TW, Lackland DT, Lewis TT, Lichtman JH, Longenecker CT, Loop MS, Lutsey PL, Martin SS, Matsushita K, Moran AE, Mussolino ME, Perak AM, Rosamond WD, Roth GA, Sampson UKA, Satou GM, Schroeder EB, Shah SH, Shay CM, Spartano NL, Stokes A, Tirschwell DL, VanWagner LB, Tsao CW. Heart Disease and Stroke Statistics-2020 Update: A Report From the American Heart Association. Circulation 2020; 141:e139-e596. [PMID: 31992061 DOI: 10.1161/cir.0000000000000757] [Citation(s) in RCA: 4636] [Impact Index Per Article: 1159.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports on the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2020 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, metrics to assess and monitor healthy diets, an enhanced focus on social determinants of health, a focus on the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors, implementation strategies, and implications of the American Heart Association's 2020 Impact Goals. RESULTS Each of the 26 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, healthcare administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Benjamin EJ, Muntner P, Alonso A, Bittencourt MS, Callaway CW, Carson AP, Chamberlain AM, Chang AR, Cheng S, Das SR, Delling FN, Djousse L, Elkind MSV, Ferguson JF, Fornage M, Jordan LC, Khan SS, Kissela BM, Knutson KL, Kwan TW, Lackland DT, Lewis TT, Lichtman JH, Longenecker CT, Loop MS, Lutsey PL, Martin SS, Matsushita K, Moran AE, Mussolino ME, O'Flaherty M, Pandey A, Perak AM, Rosamond WD, Roth GA, Sampson UKA, Satou GM, Schroeder EB, Shah SH, Spartano NL, Stokes A, Tirschwell DL, Tsao CW, Turakhia MP, VanWagner LB, Wilkins JT, Wong SS, Virani SS. Heart Disease and Stroke Statistics-2019 Update: A Report From the American Heart Association. Circulation 2019; 139:e56-e528. [PMID: 30700139 DOI: 10.1161/cir.0000000000000659] [Citation(s) in RCA: 5138] [Impact Index Per Article: 1027.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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Spartano NL, Demissie S, Himali JJ, Dukes KA, Murabito JM, Vasan RS, Beiser AS, Seshadri S. Accelerometer-determined physical activity and cognitive function in middle-aged and older adults from two generations of the Framingham Heart Study. Alzheimers Dement (N Y) 2019; 5:618-626. [PMID: 31660424 PMCID: PMC6807299 DOI: 10.1016/j.trci.2019.08.007] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
INTRODUCTION Physical activity (PA) may play a role in maintenance of cognitive function in both middle and older ages and prevention of outcomes such as dementia and Alzheimer's disease. METHODS Cross-sectional regression analyses were performed in Framingham Heart Study Third Generation (n = 1861) and Offspring (n = 909) cohort participants assessing the association of accelerometry-measured PA with cognitive function, adjusting for age, sex, accelerometer wear time, education, occupational status/PA, and smoking status. RESULTS In each cohort, achieving just 10-21.4 min/day moderate-to-vigorous PA related to better executive function (P < .02); and just 10 min/day moderate-to-vigorous PA was associated with better verbal memory in middle-aged adults in the Third Generation cohort (P = .02). In older adults of the Offspring cohort, total PA (measured in steps/day) was associated with better executive function (P < .02). DISCUSSION PA at levels lower than the current PA Guidelines (just 10 min/day moderate-to-vigorous PA and total PA including lower intensity PA) were associated with better cognitive function.
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Affiliation(s)
- Nicole L. Spartano
- Section of Endocrinology, Diabetes, Nutrition and Weight Management, Boston University School of Medicine, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Serkalem Demissie
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Jayandra J. Himali
- Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Kimberly A. Dukes
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Biostatistics and Epidemiology Data Analysis Center, Boston University School of Public Health, Boston, MA, USA
| | - Joanne M. Murabito
- Framingham Heart Study, Framingham, MA, USA
- Section of General Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Ramachandran S. Vasan
- Framingham Heart Study, Framingham, MA, USA
- Section of Preventive Medicine and Epidemiology, Section of Cardiovascular Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Alexa S. Beiser
- Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Sudha Seshadri
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
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Spartano NL, Lin H, Sun F, Lunetta KL, Trinquart L, Valentino M, Manders ES, Pletcher MJ, Marcus GM, McManus DD, Benjamin EJ, Fox CS, Olgin JE, Murabito JM. Comparison of On-Site Versus Remote Mobile Device Support in the Framingham Heart Study Using the Health eHeart Study for Digital Follow-up: Randomized Pilot Study Set Within an Observational Study Design. JMIR Mhealth Uhealth 2019; 7:e13238. [PMID: 31573928 PMCID: PMC6792023 DOI: 10.2196/13238] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Revised: 06/21/2019] [Accepted: 07/19/2019] [Indexed: 01/20/2023] Open
Abstract
Background New electronic cohort (e-Cohort) study designs provide resource-effective methods for collecting participant data. It is unclear if implementing an e-Cohort study without direct, in-person participant contact can achieve successful participation rates. Objective The objective of this study was to compare 2 distinct enrollment methods for setting up mobile health (mHealth) devices and to assess the ongoing adherence to device use in an e-Cohort pilot study. Methods We coenrolled participants from the Framingham Heart Study (FHS) into the FHS–Health eHeart (HeH) pilot study, a digital cohort with infrastructure for collecting mHealth data. FHS participants who had an email address and smartphone were randomized to our FHS-HeH pilot study into 1 of 2 study arms: remote versus on-site support. We oversampled older adults (age ≥65 years), with a target of enrolling 20% of our sample as older adults. In the remote arm, participants received an email containing a link to enrollment website and, upon enrollment, were sent 4 smartphone-connectable sensor devices. Participants in the on-site arm were invited to visit an in-person FHS facility and were provided in-person support for enrollment and connecting the devices. Device data were tracked for at least 5 months. Results Compared with the individuals who declined, individuals who consented to our pilot study (on-site, n=101; remote, n=93) were more likely to be women, highly educated, and younger. In the on-site arm, the connection and initial use of devices was ≥20% higher than the remote arm (mean percent difference was 25% [95% CI 17-35] for activity monitor, 22% [95% CI 12-32] for blood pressure cuff, 20% [95% CI 10-30] for scale, and 43% [95% CI 30-55] for electrocardiogram), with device connection rates in the on-site arm of 99%, 95%, 95%, and 84%. Once connected, continued device use over the 5-month study period was similar between the study arms. Conclusions Our pilot study demonstrated that the deployment of mobile devices among middle-aged and older adults in the context of an on-site clinic visit was associated with higher initial rates of device use as compared with offering only remote support. Once connected, the device use was similar in both groups.
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Affiliation(s)
- Nicole L Spartano
- Section of Endocrinology, Diabetes, Nutrition, and Weight Management, Boston University School of Medicine, Boston, MA, United States.,Framingham Heart Study, Framingham, MA, United States
| | - Honghuang Lin
- Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, United States
| | - Fangui Sun
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Kathryn L Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Ludovic Trinquart
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | | | | | - Mark J Pletcher
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, United States
| | - Gregory M Marcus
- Division of Hospital Medicine, University of California, San Francisco, San Francisco, CA, United States
| | - David D McManus
- Department of Medicine, University of Massachusetts Medical School, Worcester, MA, United States
| | - Emelia J Benjamin
- Framingham Heart Study, Framingham, MA, United States.,Boston University School of Medicine, Boston, MA, United States.,Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States
| | - Caroline S Fox
- Framingham Heart Study, Framingham, MA, United States.,Merck Research Laboratories, Boston, MA, United States
| | - Jeffrey E Olgin
- Division of Hospital Medicine, University of California, San Francisco, San Francisco, CA, United States
| | - Joanne M Murabito
- Framingham Heart Study, Framingham, MA, United States.,Boston University School of Medicine, Boston, MA, United States.,Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, United States
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Spartano NL, Davis-Plourde KL, Himali JJ, Andersson C, Pase MP, Maillard P, DeCarli C, Murabito JM, Beiser AS, Vasan RS, Seshadri S. Association of Accelerometer-Measured Light-Intensity Physical Activity With Brain Volume: The Framingham Heart Study. JAMA Netw Open 2019; 2:e192745. [PMID: 31002329 PMCID: PMC6481600 DOI: 10.1001/jamanetworkopen.2019.2745] [Citation(s) in RCA: 80] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Accepted: 03/04/2019] [Indexed: 12/13/2022] Open
Abstract
Importance Dementia risk may be attenuated by physical activity (PA); however, the specific activity levels optimal for dementia prevention are unclear. Moreover, most older adults are unable to meet the nationally recommended PA guidelines, set at 150 minutes of moderate to vigorous PA per week. Objective To assess the association of total steps walked per day and total dose (intensity × duration) of PA with brain volumes on magnetic resonance imaging (MRI) among Framingham Heart Study participants. Design, Setting, and Participants This cross-sectional, community-based cohort study of the association of accelerometry-determined PA with brain MRI measures in Framingham, Massachusetts, included the Framingham Heart Study third-generation (examination 2, 2008-2011) and offspring (examination 9, 2011-2014) cohorts. Of 4021 participants who agreed to wear an accelerometer and had valid data (≥10 hours/day for ≥3 days), 1667 participants who did not undergo brain MRI (n = 1604) or had prevalent dementia or stroke (n = 63) were excluded. Data analysis began in 2016 and was completed in February 2019. Exposures Physical activity achieved using accelerometry-derived total activity (steps per day) and 2 intensity levels (light intensity and moderate to vigorous intensity). Main Outcomes and Measures Differences in total brain volume and other MRI markers of brain aging. Results The study sample of 2354 participants had a mean (SD) age of 53 (13) years, 1276 (54.2%) were women, and 1099 (46.7%) met the PA guidelines. Incremental light-intensity PA was associated with higher total brain volume; each additional hour of light-intensity PA was associated with approximately 1.1 years less brain aging (β estimate, 0.22; SD, 0.07; P = .003). Among individuals not meeting the PA guidelines, each hour of light-intensity PA (β estimate, 0.28; SD, 0.11; P = .01) and achieving 7500 steps or more per day (β estimate, 0.44; SD, 0.18; P = .02) were associated with higher total brain volume, equivalent to approximately 1.4 to 2.2 years less brain aging. After adjusting for light-intensity PA, neither increasing moderate to vigorous PA levels nor meeting the threshold moderate to vigorous PA level recommended by the PA guidelines were significantly associated with total brain volume. Conclusions and Relevance Every additional hour of light-intensity PA was associated with higher brain volumes, even among individuals not meeting current PA guidelines. These data are consistent with the notion that the potential benefits of PA on brain aging may accrue at a lower, more achievable level of intensity or duration.
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Affiliation(s)
- Nicole L. Spartano
- Department of Endocrinology, Diabetes, Nutrition and Weight Management, Boston University School of Medicine, Boston, Massachusetts
- Framingham Heart Study, Framingham, Massachusetts
| | - Kendra L. Davis-Plourde
- Framingham Heart Study, Framingham, Massachusetts
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Jayandra J. Himali
- Framingham Heart Study, Framingham, Massachusetts
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
| | - Charlotte Andersson
- Framingham Heart Study, Framingham, Massachusetts
- Department of Internal Medicine, Glostrup Hospital, Glostrup, Denmark
| | - Matthew P. Pase
- Framingham Heart Study, Framingham, Massachusetts
- Melbourne Dementia Research Centre, The Florey Institute for Neuroscience and Mental Health, Melbourne, Victoria, Australia
- Faculty of Medicine, Dentistry, and Health Sciences, The University of Melbourne, Melbourne, Victoria, Australia
- Centre for Human Psychopharmacology, Swinburne University of Technology, Melbourne, Victoria, Australia
| | - Pauline Maillard
- Department of Neurology and Center for Neuroscience, University of California, Davis
| | - Charles DeCarli
- Department of Neurology and Center for Neuroscience, University of California, Davis
| | - Joanne M. Murabito
- Framingham Heart Study, Framingham, Massachusetts
- Department of Medicine, Boston University School of Medicine, Boston, Massachusetts
| | - Alexa S. Beiser
- Framingham Heart Study, Framingham, Massachusetts
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
| | - Ramachandran S. Vasan
- Framingham Heart Study, Framingham, Massachusetts
- Department of Medicine, Boston University School of Medicine, Boston, Massachusetts
- Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts
| | - Sudha Seshadri
- Framingham Heart Study, Framingham, Massachusetts
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio
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McManus DD, Trinquart L, Benjamin EJ, Manders ES, Fusco K, Jung LS, Spartano NL, Kheterpal V, Nowak C, Sardana M, Murabito JM. Design and Preliminary Findings From a New Electronic Cohort Embedded in the Framingham Heart Study. J Med Internet Res 2019; 21:e12143. [PMID: 30821691 PMCID: PMC6418484 DOI: 10.2196/12143] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2018] [Revised: 01/10/2019] [Accepted: 01/21/2019] [Indexed: 12/26/2022] Open
Abstract
Background New models of scalable population-based data collection that integrate digital and mobile health (mHealth) data are necessary. Objective The aim of this study was to describe a cardiovascular digital and mHealth electronic cohort (e-cohort) embedded in a traditional longitudinal cohort study, the Framingham Heart Study (FHS). Methods We invited eligible and consenting FHS Generation 3 and Omni participants to download the electronic Framingham Heart Study (eFHS) app onto their mobile phones and co-deployed a digital blood pressure (BP) cuff. Thereafter, participants were also offered a smartwatch (Apple Watch). Participants are invited to complete surveys through the eFHS app, to perform weekly BP measurements, and to wear the smartwatch daily. Results Up to July 2017, we enrolled 790 eFHS participants, representing 76% (790/1044) of potentially eligible FHS participants. eFHS participants were, on average, 53±8 years of age and 57% were women. A total of 85% (675/790) of eFHS participants completed all of the baseline survey and 59% (470/790) completed the 3-month survey. A total of 42% (241/573) and 76% (306/405) of eFHS participants adhered to weekly digital BP and heart rate (HR) uploads, respectively, over 12 weeks. Conclusions We have designed an e-cohort focused on identifying novel cardiovascular disease risk factors using a new smartphone app, a digital BP cuff, and a smartwatch. Despite minimal training and support, preliminary findings over a 3-month follow-up period show that uptake is high and adherence to periodic app-based surveys, weekly digital BP assessments, and smartwatch HR measures is acceptable.
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Affiliation(s)
- David D McManus
- Cardiology Division, Department of Medicine, University of Massachusetts Medical School, Worcester, MA, United States.,Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, United States.,Department of Medicine, University of Massachusetts Medical School, Worcester, MA, United States
| | - Ludovic Trinquart
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States.,Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Emelia J Benjamin
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States.,Section of Preventive Medicine and Epidemiology and Section of Cardiovascular Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, United States.,Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States
| | - Emily S Manders
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States
| | - Kelsey Fusco
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States
| | - Lindsey S Jung
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Nicole L Spartano
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States.,Section of Endocrinology, Diabetes, Nutrition, and Weight Management, Boston University School of Medicine, Boston, MA, United States
| | | | | | - Mayank Sardana
- Cardiology Division, Department of Medicine, University of California San Francisco, San Francisco, CA, United States
| | - Joanne M Murabito
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, United States.,Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, United States
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Spartano NL, Davis-Plourde KL, Himali JJ, Murabito JM, Vasan RS, Beiser AS, Seshadri S. Self-Reported Physical Activity and Relations to Growth and Neurotrophic Factors in Diabetes Mellitus: The Framingham Offspring Study. J Diabetes Res 2019; 2019:2718465. [PMID: 30729134 PMCID: PMC6343169 DOI: 10.1155/2019/2718465] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2018] [Revised: 11/28/2018] [Accepted: 12/03/2018] [Indexed: 01/02/2023] Open
Abstract
AIMS Circulating insulin-like growth factor- (IGF-) 1, vascular endothelial growth factor (VEGF), and brain-derived neurotrophic factor (BDNF) levels are often lower in individuals with diabetes mellitus (DM) and are important for repairing vascular and neuronal dysfunction. The purpose of this investigation was to determine the cross-sectional relations of physical activity to circulating concentrations of IGF-1, VEGF, and BDNF in individuals with and without DM. METHODS In 1730 participants from the Framingham Offspring Study examination cycle 7, including those with DM (n = 179, mean age 64 years, 39% women) and without DM (n = 1551, mean age 60 years, 46% women), we related self-reported physical activity variables to circulating concentrations of IGF-1, VEGF, and BDNF using linear multivariable regression models. We also tested for interactions by age. Participants with prevalent cardiovascular disease, stroke, and dementia or taking hormone replacement therapy were excluded. RESULTS In participants with DM, more ambulatory physical activity was associated with higher IGF-1 levels (β ± standard error (SE) = 0.22 ± 0.08, p = 0.009), and more total physical activity was related to higher BDNF levels (β ± SE = 0.18 ± 0.08, p = 0.035), but physical activity was not significantly related to circulating VEGF. In participants without DM, no associations were observed. Moreover, in the examination of interactions by age, the association of ambulatory physical activity with IGF-1 levels was only observed in older adults with DM (age ≥ 60 years, β ± SE = 0.23 ± 0.11, p = 0.042) but not in middle-aged adults with DM (age < 60 years, β ± SE = 0.06 ± 0.13, p = 0.645). CONCLUSION Our results suggest that more physical activity is associated with higher circulating IGF-1 and BDNF in participants with DM. These results, dissecting interactions by both age and DM status, may also help to explain some of the inconsistent results in studies relating physical activity to growth and neurotrophic factors.
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Affiliation(s)
- Nicole L. Spartano
- Department of Endocrinology, Diabetes, Nutrition & Weight Management, Boston University School of Medicine (BUSM), Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Kendra L. Davis-Plourde
- Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health (BUSPH), Boston, MA, USA
| | - Jayandra J. Himali
- Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health (BUSPH), Boston, MA, USA
- Department of Neurology, BUSM, Boston, MA, USA
| | - Joanne M. Murabito
- Framingham Heart Study, Framingham, MA, USA
- Departments of Medicine and Epidemiology, BUSM and BUSPH, Boston, MA, USA
| | - Ramachandran S. Vasan
- Framingham Heart Study, Framingham, MA, USA
- Departments of Medicine and Epidemiology, BUSM and BUSPH, Boston, MA, USA
| | - Alexa S. Beiser
- Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health (BUSPH), Boston, MA, USA
- Department of Neurology, BUSM, Boston, MA, USA
| | - Sudha Seshadri
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, BUSM, Boston, MA, USA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
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Affiliation(s)
- Nicole L Spartano
- From the Section of Endocrinology, Diabetes, Nutrition & Weight Management (N.L.S.), Boston University School of Medicine, MA; and Florey Institute of Neuroscience and Mental Health (J.B.), University of Melbourne, Heidelberg, Victoria, Australia.
| | - Julie Bernhardt
- From the Section of Endocrinology, Diabetes, Nutrition & Weight Management (N.L.S.), Boston University School of Medicine, MA; and Florey Institute of Neuroscience and Mental Health (J.B.), University of Melbourne, Heidelberg, Victoria, Australia
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Riffenburg KM, Spartano NL. Physical activity and weight maintenance: the utility of wearable devices and mobile health technology in research and clinical settings. Curr Opin Endocrinol Diabetes Obes 2018; 25:310-314. [PMID: 30063553 DOI: 10.1097/med.0000000000000433] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
PURPOSE OF REVIEW The integration of wearable devices and mobile health (mHealth) technology to facilitate behavior change has the potential to transform the efficacy of interventions and implementation programs for weight maintenance. The purpose of this review was to provide a comprehensive analysis of the overall utility of wearable devices for assessing and promoting weight maintenance in research and clinical settings. RECENT FINDINGS Recent intervention trials using wearable devices have been successful in increasing physical activity and decreasing or maintaining body weight, but complex study designs involving multiple behavioral strategies make it difficult to assess whether wearable devices can independently influence weight status. The daily feedback that wearable devices and mHealth technology provide may assist in motivating higher levels of physical activity achievement. However, the integration of wearable devices into the healthcare setting and implementation of mHealth programs still need to be tested. SUMMARY Recent studies add concrete implications for providers and researchers to better assess and promote physical activity in healthcare settings by identifying how wearable devices can be advantageous for physical activity and health promotion.
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Affiliation(s)
| | - Nicole L Spartano
- Section of Endocrinology, Diabetes, Nutrition, and Weight Management, Boston University School of Medicine, Boston, Massachusetts, USA
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Affiliation(s)
- Nicole L Spartano
- From the Section of Preventative Medicine and Epidemiology (N.L.S.), Boston University School of Medicine, MA; Chronic Disease Prevention Unit (T.N.), National Institute for Health and Welfare, Helsinki, Finland; and Karolinska Institutet Center for Alzheimer Research (T.N.), Stockholm, Sweden.
| | - Tiia Ngandu
- From the Section of Preventative Medicine and Epidemiology (N.L.S.), Boston University School of Medicine, MA; Chronic Disease Prevention Unit (T.N.), National Institute for Health and Welfare, Helsinki, Finland; and Karolinska Institutet Center for Alzheimer Research (T.N.), Stockholm, Sweden
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Benjamin EJ, Virani SS, Callaway CW, Chamberlain AM, Chang AR, Cheng S, Chiuve SE, Cushman M, Delling FN, Deo R, de Ferranti SD, Ferguson JF, Fornage M, Gillespie C, Isasi CR, Jiménez MC, Jordan LC, Judd SE, Lackland D, Lichtman JH, Lisabeth L, Liu S, Longenecker CT, Lutsey PL, Mackey JS, Matchar DB, Matsushita K, Mussolino ME, Nasir K, O'Flaherty M, Palaniappan LP, Pandey A, Pandey DK, Reeves MJ, Ritchey MD, Rodriguez CJ, Roth GA, Rosamond WD, Sampson UKA, Satou GM, Shah SH, Spartano NL, Tirschwell DL, Tsao CW, Voeks JH, Willey JZ, Wilkins JT, Wu JH, Alger HM, Wong SS, Muntner P. Heart Disease and Stroke Statistics-2018 Update: A Report From the American Heart Association. Circulation 2018; 137:e67-e492. [PMID: 29386200 DOI: 10.1161/cir.0000000000000558] [Citation(s) in RCA: 4390] [Impact Index Per Article: 731.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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Heffernan KS, Augustine JA, Lefferts WK, Spartano NL, Hughes WE, Jorgensen RS, Gump BB. Arterial stiffness and cerebral hemodynamic pulsatility during cognitive engagement in younger and older adults. Exp Gerontol 2018; 101:54-62. [DOI: 10.1016/j.exger.2017.11.004] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2017] [Accepted: 11/07/2017] [Indexed: 11/17/2022]
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Tan ZS, Spartano NL, Beiser AS, DeCarli C, Auerbach SH, Vasan RS, Seshadri S. Physical Activity, Brain Volume, and Dementia Risk: The Framingham Study. J Gerontol A Biol Sci Med Sci 2017; 72:789-795. [PMID: 27422439 DOI: 10.1093/gerona/glw130] [Citation(s) in RCA: 66] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2015] [Accepted: 06/19/2016] [Indexed: 11/14/2022] Open
Abstract
Background Several longitudinal studies found an inverse relationship between levels of physical activity and cognitive decline, dementia, and/or Alzheimer's disease (AD), but results have been inconsistent. We followed an older, community-based cohort for over a decade to examine the association of physical activity with the risk of incident dementia and subclinical brain MRI markers of dementia. Methods The physical activity index (PAI) was assessed in the Framingham Study Original and Offspring cohorts, aged 60 years or older. We examined the association between PAI and risk of incident all-cause dementia and AD in participants of both cohorts who were cognitively intact and had available PAI (n = 3,714; 54% women; mean age = 70±7 years). We additionally examined the association between PAI and brain MRI in the Offspring cohort (n = 1,987). Results Over a decade of follow-up, 236 participants developed dementia (188 AD). Participants in the lowest quintile of PAI had an increased risk of incident dementia compared with those in higher quintiles (hazard ratio [HR] = 1.50, 95% confidence interval [CI] = 1.04-1.97, p = .028) in a multivariable-adjusted model. Secondary analysis revealed that this relation was limited to participants who were apolipoprotein (APO)E ε4 allele noncarriers (HR = 1.58, 95% CI = 1.08-2.32; p = .018) and strongest in participants aged 75 years or older. PAI was also linearly related to total brain and hippocampal volumes (β ± SE = 0.24±0.06; p < .01 and 0.004±0.001; p = .003, respectively). Conclusion Low physical activity is associated with a higher risk for dementia in older individuals, suggesting that a reduced risk of dementia and higher brain volumes may be additional health benefits of maintaining physical activity into old age.
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Affiliation(s)
- Zaldy S Tan
- Division of Geriatric Medicine, Department of Medicine, David Geffen School of Medicine, University of California Los Angeles.,The Framingham Heart Study, Massachusetts
| | - Nicole L Spartano
- The Framingham Heart Study, Massachusetts.,Section of Preventative Medicine and Epidemiology and
| | - Alexa S Beiser
- The Framingham Heart Study, Massachusetts.,Department of Neurology, Boston University School of Medicine, Massachusetts.,Department of Biostatistics, Boston University School of Public Health, Massachusetts
| | | | - Sanford H Auerbach
- The Framingham Heart Study, Massachusetts.,Department of Neurology, Boston University School of Medicine, Massachusetts
| | - Ramachandran S Vasan
- The Framingham Heart Study, Massachusetts.,Section of Preventative Medicine and Epidemiology and
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Spartano NL, Stevenson MD, Xanthakis V, Larson MG, Andersson C, Murabito JM, Vasan RS. Associations of objective physical activity with insulin sensitivity and circulating adipokine profile: the Framingham Heart Study. Clin Obes 2017; 7:59-69. [PMID: 28112860 PMCID: PMC5339058 DOI: 10.1111/cob.12177] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Revised: 10/21/2016] [Accepted: 12/07/2016] [Indexed: 12/19/2022]
Abstract
The purpose of this study was to explore the relation of physical activity (PA) and sedentary time (SED) to insulin sensitivity and adipokines. We assessed PA and SED using Actical accelerometers and insulin resistance (HOMA-IR) in 2109 participants (free of type 1 and 2 diabetes mellitus) from Framingham Generation 3 and Omni 2 cohorts (mean age 46 years, 54% women). Systemic inflammation (C-reactive protein [CRP]) and circulating adipokines were measured 6 years earlier. Steps per day, moderate-to-vigorous PA (MVPA) and SED per wear time (%SED) were predictor variables in multivariable regression analyses, with HOMA-IR, CRP and circulating adipokines as outcome measures. We reported that higher MVPA and more steps per day were associated with lower HOMA-IR, adjusting for %SED (β = -0.036, P = 0.002; β = -0.041, P = 0.005). Steps were inversely associated with CRP, but were directly associated with insulin-like growth factor (IGF)-1 levels (β = -0.111, P = 0.002; β = 3.293, P = 0.007). %SED was positively associated with HOMA-IR (β = 0.033, P < 0.0001), but non-significant after adjusting for MVPA (P = 0.13). %SED was associated with higher ratio of leptin/leptin receptor (sOB-R) and higher adipocyte fatty acid-binding protein (FABP)4 (β = 0.096, P < 0.0001; β = 0.593, P = 0.002). Our findings suggest differential influences of PA vs. SED on metabolic pathways, with PA modulating insulin resistance and inflammation, whereas SED influences FABPs.
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Affiliation(s)
- N L Spartano
- Sections of Preventive Medicine and Epidemiology, and Cardiology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - M D Stevenson
- Framingham Heart Study, Framingham, MA, USA
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - V Xanthakis
- Sections of Preventive Medicine and Epidemiology, and Cardiology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - M G Larson
- Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - C Andersson
- Framingham Heart Study, Framingham, MA, USA
- Department of Internal Medicine, Glostrup Hospital, Glostrup, Denmark
| | - J M Murabito
- Framingham Heart Study, Framingham, MA, USA
- Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - R S Vasan
- Sections of Preventive Medicine and Epidemiology, and Cardiology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
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Spartano NL, Heffernan KS, Dumas AK, Gump BB. Accelerometer-determined physical activity and the cardiovascular response to mental stress in children. J Sci Med Sport 2017; 20:60-65. [PMID: 27283342 PMCID: PMC5133178 DOI: 10.1016/j.jsams.2016.05.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2016] [Revised: 04/22/2016] [Accepted: 05/26/2016] [Indexed: 10/21/2022]
Abstract
OBJECTIVES Cardiovascular reactivity has been associated with future hypertension and cardiovascular mortality. Higher physical activity (PA) has been associated with lower cardiovascular reactivity in adults, but little data is available in children. The purpose of this study was to examine the relationship between PA and cardiovascular reactivity to mental stress in children. DESIGN Cross-sectional study. METHODS This study sample included children from the Oswego Lead Study (n=79, 46% female, 9-11 years old). Impedance cardiography was performed while children participated in a stress response protocol. Children were also asked to wear Actigraph accelerometers on their wrists for 3 days to measure intensity and duration of PA and sedentary time. RESULTS In multivariable models, moderate to vigorous (MV) PA was associated with lower body mass index (BMI) percentile and lower total peripheral resistance (TPR) response to stress (beta=-0.025, p=0.02; beta=-0.009, p=0.05). After additional adjustment for BMI, MVPA was also associated with lower diastolic blood pressure response to stress (beta=-0.01, p=0.03). Total PA and sedentary time were not associated with BMI or cardiovascular responses to stress. CONCLUSIONS A modest, inverse relation of PA to vascular reactivity to mental stress was observed in children. These data provide confirmatory evidence that the promotion of PA recommendations for children are important for cardiovascular health.
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Affiliation(s)
- Nicole L Spartano
- Section of Preventative Medicine and Epidemiology, Boston University School of Medicine, Boston, MA, United States; The Whitaker Cardiovascular Institute, Boston University School of Medicine, Boston, MA, United States.
| | - Kevin S Heffernan
- Department of Exercise Science, Syracuse University, Syracuse, NY, United States
| | - Amy K Dumas
- Department of Public Health, Food Studies, and Nutrition, Syracuse University, Syracuse, NY, United States
| | - Brooks B Gump
- Department of Public Health, Food Studies, and Nutrition, Syracuse University, Syracuse, NY, United States
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Spartano NL, Lyass A, Larson MG, Lewis GD, Vasan RS. Submaximal Exercise Systolic Blood Pressure and Heart Rate at 20 Years of Follow-up: Correlates in the Framingham Heart Study. J Am Heart Assoc 2016; 5:JAHA.115.002821. [PMID: 27233297 PMCID: PMC4937245 DOI: 10.1161/jaha.115.002821] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background Beyond their resting values, exercise responses in blood pressure (BP) and heart rate (HR) may add prognostic information for cardiovascular disease (CVD). In cross‐sectional studies, exercise BP and HR responses correlate with CVD risk factors; however, it is unclear which factors influence longitudinal changes in exercise responses over time, which is important for our understanding of the development of CVD. Methods and Results We assessed BP and HR responses to low‐level exercise tests (6‐minute Bruce protocol) in 1231 Framingham Offspring participants (55% women) who underwent a routine treadmill test in 1979–1983 (baseline; mean age 39±8 years) that was repeated in 1998–2001 (follow‐up; mean age 58±8 years). Adjusting for baseline exercise responses, we related the follow‐up exercise responses to baseline CVD risk factors and to their changes between examinations. Compared with men, women had greater rise in exercise systolic (S)BP and HR at 20‐year follow‐up (both P<0.005). Baseline blood lipid levels, resting SBP and HR, and smoking status were associated with greater exercise SBP at follow‐up (all P<0.05). Weight gain across examinations was associated with higher exercise SBP and HR at follow‐up (both P<0.0001). Smoking cessation was associated with a 53% reduced risk of attaining the highest quartile of exercise SBP (≥180 mm Hg) at follow‐up (P<0.05). Conclusion An adverse CVD risk factor profile in young adults and its worsening over time were associated with higher SBP and HR responses to low‐level exercise in midlife. Maintaining or adopting a healthy risk factor profile may favorably impact the exercise responses over time.
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Affiliation(s)
- Nicole L Spartano
- Sections of Preventative Medicine and Epidemiology, and Cardiology, Department of Medicine, Boston University School of Medicine, Boston, MA The Whitaker Cardiovascular Institute, Boston University School of Medicine, Boston, MA
| | - Asya Lyass
- Framingham Heart Study, Framingham, MA Department of Mathematics and Statistics, Boston University, Boston, MA
| | - Martin G Larson
- Framingham Heart Study, Framingham, MA Department of Mathematics and Statistics, Boston University, Boston, MA Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Gregory D Lewis
- Cardiology Division, Massachusetts General Hospital, Harvard Medical School, Cambridge, MA Pulmonary and Critical Care Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA Broad Institute of MIT and Harvard, Cambridge, MA
| | - Ramachandran S Vasan
- Sections of Preventative Medicine and Epidemiology, and Cardiology, Department of Medicine, Boston University School of Medicine, Boston, MA Framingham Heart Study, Framingham, MA Department of Epidemiology, Boston University School of Public Health, Boston, MA
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Spartano NL, Himali JJ, Beiser AS, Lewis GD, DeCarli C, Vasan RS, Seshadri S. Midlife exercise blood pressure, heart rate, and fitness relate to brain volume 2 decades later. Neurology 2016; 86:1313-1319. [PMID: 26865519 DOI: 10.1212/wnl.0000000000002415] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2015] [Accepted: 12/14/2015] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To determine whether poor cardiovascular (CV) fitness and exaggerated exercise blood pressure (BP) and heart rate (HR) were associated with worse brain morphology in later life. METHODS Framingham Offspring participants (n = 1,094, 53.9% female) free from dementia and CV disease (CVD) underwent an exercise treadmill test at a mean age of 40 ± 9 years. A second treadmill test and MRI scans of the brain were administered 2 decades later at mean age of 58 ± 8 years. RESULTS Poor CV fitness and greater diastolic BP and HR response to exercise at baseline were associated with a smaller total cerebral brain volume (TCBV) almost 2 decades later (all p < 0.05) in multivariable adjusted models; the effect of 1 SD lower fitness was equivalent to approximately 1 additional year of brain aging in individuals free of CVD. In participants with prehypertension or hypertension at baseline, exercise systolic BP was also associated with smaller TCBV (p < 0.05). CONCLUSION Our results suggest that lower CV fitness and exaggerated exercise BP and HR responses in middle-aged adults are associated with smaller brain volume nearly 2 decades later. Promotion of midlife CV fitness may be an important step towards ensuring healthy brain aging.
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Affiliation(s)
- Nicole L Spartano
- From the Section of Preventive Medicine and Epidemiology (N.L.S., R.S.V.), The Whitaker Cardiovascular Institute (N.L.S.), and Department of Neurology (J.J.H., A.S.B., S.S.), Boston University School of Medicine; the Framingham Heart Study (N.L.S., J.J.H., A.S.B., R.S.V., S.S.); Departments of Biostatistics (A.S.B.) and Epidemiology (R.S.V.), Boston University School of Public Health; Cardiology Division (G.D.L.) and the Pulmonary and Critical Care Unit (G.D.L.), Massachusetts General Hospital, Harvard Medical School; Broad Institute of MIT & Harvard (G.D.L.), Cambridge, MA; and Department of Neurology and Center for Neuroscience (C.D.), University of California at Davis.
| | - Jayandra J Himali
- From the Section of Preventive Medicine and Epidemiology (N.L.S., R.S.V.), The Whitaker Cardiovascular Institute (N.L.S.), and Department of Neurology (J.J.H., A.S.B., S.S.), Boston University School of Medicine; the Framingham Heart Study (N.L.S., J.J.H., A.S.B., R.S.V., S.S.); Departments of Biostatistics (A.S.B.) and Epidemiology (R.S.V.), Boston University School of Public Health; Cardiology Division (G.D.L.) and the Pulmonary and Critical Care Unit (G.D.L.), Massachusetts General Hospital, Harvard Medical School; Broad Institute of MIT & Harvard (G.D.L.), Cambridge, MA; and Department of Neurology and Center for Neuroscience (C.D.), University of California at Davis
| | - Alexa S Beiser
- From the Section of Preventive Medicine and Epidemiology (N.L.S., R.S.V.), The Whitaker Cardiovascular Institute (N.L.S.), and Department of Neurology (J.J.H., A.S.B., S.S.), Boston University School of Medicine; the Framingham Heart Study (N.L.S., J.J.H., A.S.B., R.S.V., S.S.); Departments of Biostatistics (A.S.B.) and Epidemiology (R.S.V.), Boston University School of Public Health; Cardiology Division (G.D.L.) and the Pulmonary and Critical Care Unit (G.D.L.), Massachusetts General Hospital, Harvard Medical School; Broad Institute of MIT & Harvard (G.D.L.), Cambridge, MA; and Department of Neurology and Center for Neuroscience (C.D.), University of California at Davis
| | - Gregory D Lewis
- From the Section of Preventive Medicine and Epidemiology (N.L.S., R.S.V.), The Whitaker Cardiovascular Institute (N.L.S.), and Department of Neurology (J.J.H., A.S.B., S.S.), Boston University School of Medicine; the Framingham Heart Study (N.L.S., J.J.H., A.S.B., R.S.V., S.S.); Departments of Biostatistics (A.S.B.) and Epidemiology (R.S.V.), Boston University School of Public Health; Cardiology Division (G.D.L.) and the Pulmonary and Critical Care Unit (G.D.L.), Massachusetts General Hospital, Harvard Medical School; Broad Institute of MIT & Harvard (G.D.L.), Cambridge, MA; and Department of Neurology and Center for Neuroscience (C.D.), University of California at Davis
| | - Charles DeCarli
- From the Section of Preventive Medicine and Epidemiology (N.L.S., R.S.V.), The Whitaker Cardiovascular Institute (N.L.S.), and Department of Neurology (J.J.H., A.S.B., S.S.), Boston University School of Medicine; the Framingham Heart Study (N.L.S., J.J.H., A.S.B., R.S.V., S.S.); Departments of Biostatistics (A.S.B.) and Epidemiology (R.S.V.), Boston University School of Public Health; Cardiology Division (G.D.L.) and the Pulmonary and Critical Care Unit (G.D.L.), Massachusetts General Hospital, Harvard Medical School; Broad Institute of MIT & Harvard (G.D.L.), Cambridge, MA; and Department of Neurology and Center for Neuroscience (C.D.), University of California at Davis
| | - Ramachandran S Vasan
- From the Section of Preventive Medicine and Epidemiology (N.L.S., R.S.V.), The Whitaker Cardiovascular Institute (N.L.S.), and Department of Neurology (J.J.H., A.S.B., S.S.), Boston University School of Medicine; the Framingham Heart Study (N.L.S., J.J.H., A.S.B., R.S.V., S.S.); Departments of Biostatistics (A.S.B.) and Epidemiology (R.S.V.), Boston University School of Public Health; Cardiology Division (G.D.L.) and the Pulmonary and Critical Care Unit (G.D.L.), Massachusetts General Hospital, Harvard Medical School; Broad Institute of MIT & Harvard (G.D.L.), Cambridge, MA; and Department of Neurology and Center for Neuroscience (C.D.), University of California at Davis
| | - Sudha Seshadri
- From the Section of Preventive Medicine and Epidemiology (N.L.S., R.S.V.), The Whitaker Cardiovascular Institute (N.L.S.), and Department of Neurology (J.J.H., A.S.B., S.S.), Boston University School of Medicine; the Framingham Heart Study (N.L.S., J.J.H., A.S.B., R.S.V., S.S.); Departments of Biostatistics (A.S.B.) and Epidemiology (R.S.V.), Boston University School of Public Health; Cardiology Division (G.D.L.) and the Pulmonary and Critical Care Unit (G.D.L.), Massachusetts General Hospital, Harvard Medical School; Broad Institute of MIT & Harvard (G.D.L.), Cambridge, MA; and Department of Neurology and Center for Neuroscience (C.D.), University of California at Davis
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Weinstein G, Preis SR, Beiser AS, Satizabal CL, Spartano NL, Chen TC, Ramachandran VS, Seshadri S. P3‐081: Associations between BDNF serum levels and Alzheimer's disease‐related measures: The framingham study. Alzheimers Dement 2015. [DOI: 10.1016/j.jalz.2015.06.948] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
| | - Sarah R. Preis
- Boston University School of Public HealthBostonMAUSA
- The Framingham StudyFraminghamMAUSA
| | - Alexa S. Beiser
- Boston University School of Public HealthBostonMAUSA
- The Framingham StudyFraminghamMAUSA
| | - Claudia L. Satizabal
- Boston University School of MedicineBostonMAUSA
- The Framingham Heart StudyFraminghamMAUSA
| | | | - Tai C. Chen
- Boston University School of MedicineBostonMAUSA
| | - Vasan S. Ramachandran
- Boston University School of MedicineBostonMAUSA
- The Framingham Heart StudyFraminghamMAUSA
| | - Sudha Seshadri
- Boston University School of MedicineBostonMAUSA
- The Framingham Heart StudyFraminghamMAUSA
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Augustine JA, Lefferts WK, Spartano NL, Hughes WE, Gump BB, Heffernan KS. Physical Function, Cognitive Function and Aortic Stiffness in Older Adults. Med Sci Sports Exerc 2015. [DOI: 10.1249/01.mss.0000479035.29323.55] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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Heffernan KS, Spartano NL, Augustine JA, Lefferts WK, Hughes WE, Mitchell GF, Jorgensen RS, Gump BB. Carotid artery stiffness and hemodynamic pulsatility during cognitive engagement in healthy adults: a pilot investigation. Am J Hypertens 2015; 28:615-22. [PMID: 25384407 DOI: 10.1093/ajh/hpu198] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2014] [Accepted: 09/10/2014] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND The matching of vascular supply to neuronal metabolic demand during cognitive engagement is known as neurovascular coupling (NVC). Arterial stiffness is a prominent determinant of pulsatility in the systemic circulation and may thus indirectly impact NVC. In this pilot investigation, we explored changes in carotid artery stiffness and cerebrovascular hemodynamic pulsatiltiy during cognitive engagement in healthy adults. METHODS Twenty-seven adults (age 39 ± 3 years, BMI 24 ± 1 kg/m(2)) underwent Doppler ultrasonography of the common carotid artery (CCA) combined with applanation tonometry to derive (i) CCA elastic modulus (Ep) and β-stiffness index; (ii) CCA flow pulsatility index (PI); (iii) CCA pulse pressure, (iv) CCA augmentation index (AIx). Cerebral PI was assessed using transcranial Doppler at the middle cerebral artery (MCA). All measures were made at rest and during an incongruent Stroop task. RESULTS CCA PI was reduced (1.75 ± 0.06 to 1.57 ± 0.06, P < 0.05) while MCA PI was unchanged (0.75 ± 0.02 to 0.75 ± 0.02, P > 0.05) during Stroop. Brachial pulse pressure increased during Stroop (43 ± 1 to 46 ± 1 mm Hg, P < 0.05) while CCA pulse pressure was unchanged (36 ± 1 to 35 ± 1 mm Hg, P > 0.05). Similarly, CCA Ep (54.5 ± 5.5 to 53.8 ± 4.9 kPa, P > 0.05) and β-stiffness index (4.4 ± 0.4 to 4.2 ± 0.3 aU, P > 0.05) were unchanged. CCA AIx increased (1 ± 4 to 13 ± 4%, P < 0.05). CONCLUSION Carotid pressure pulsatility is unaltered while carotid flow pulsatility is reduced during cognitive engagement. Carotid artery stiffness does not change suggesting that factors other than the dynamic elastic properties of the CCA buffer cerebrovascular hemodynamic pulsatility during cognitive engagement.
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Affiliation(s)
- Kevin S Heffernan
- Department of Exercise Science, Syracuse University, Syracuse, New York, USA;
| | - Nicole L Spartano
- Department of Exercise Science, Syracuse University, Syracuse, New York, USA
| | | | - Wesley K Lefferts
- Department of Exercise Science, Syracuse University, Syracuse, New York, USA
| | - William E Hughes
- Department of Exercise Science, Syracuse University, Syracuse, New York, USA
| | - Gary F Mitchell
- Cardiovascular Engineering, Inc., Norwood, Massachusetts, USA
| | | | - Brooks B Gump
- Department of Public Health, Syracuse University, Syracuse, New York, USA
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Andersson C, Lyass A, Larson MG, Spartano NL, Vita JA, Benjamin EJ, Murabito JM, Esliger DW, Blease SJ, Hamburg NM, Mitchell GF, Vasan RS. Physical activity measured by accelerometry and its associations with cardiac structure and vascular function in young and middle-aged adults. J Am Heart Assoc 2015; 4:e001528. [PMID: 25792127 PMCID: PMC4392434 DOI: 10.1161/jaha.114.001528] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
BACKGROUND Physical activity is associated with several health benefits, including lower cardiovascular disease risk. The independent influence of physical activity on cardiac and vascular function in the community, however, has been sparsely investigated. MEASURES AND RESULTS We related objective measures of moderate- to vigorous-intensity physical activity (MVPA, assessed by accelerometry) to cardiac and vascular indices in 2376 participants of the Framingham Heart Study third generation cohort (54% women, mean age 47 years). Using multivariable regression models, we related MVPA to the following echocardiographic and vascular measures: left ventricular mass, left atrial and aortic root sizes, carotid-femoral pulse wave velocity, augmentation index, and forward pressure wave. Men and women engaged in MVPA 29.9±21.4 and 25.5±19.4 min/day, respectively. Higher values of MVPA (per 10-minute increment) were associated with lower carotid-femoral pulse wave velocity (estimate -0.53 ms/m; P=0.006) and lower forward pressure wave (estimate -0.23 mm Hg; P=0.03) but were not associated with augmentation index (estimate 0.13%; P=0.25). MVPA was associated positively with log(e) left ventricular mass (estimate 0.006 log(e) [g/m(2)]; P=0.0003), left ventricular wall thickness (estimate 0.07 mm; P=0.0001), and left atrial dimension (estimate 0.10 mm; P=0.01). MVPA also tended to be positively associated with aortic root dimension (estimate 0.05 mm; P=0.052). Associations of MVPA with cardiovascular measures were similar, in general, for bouts lasting <10 versus ≥10 minutes. CONCLUSIONS In our community-based sample, greater physical activity was associated with lower vascular stiffness but with higher echocardiographic left ventricular mass and left atrial size. These findings suggest complex relations of usual levels of physical activity and cardiovascular remodeling.
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Affiliation(s)
- Charlotte Andersson
- Framingham Heart Study, Framingham, MA (C.A., A.L., M.G.L., E.J.B., J.M.M., S.J.B., R.S.V.) Department of Epidemiology, Boston University School of Public Health, Boston, MA (C.A., N.L.S., E.J.B., J.M.M., R.S.V.) Department of Cardiology, Gentofte Hospital, University of Copenhagen, Denmark (C.A.)
| | - Asya Lyass
- Framingham Heart Study, Framingham, MA (C.A., A.L., M.G.L., E.J.B., J.M.M., S.J.B., R.S.V.) Department of Mathematics and Statistics, Boston University, Boston, MA (A.L., M.G.L.)
| | - Martin G Larson
- Framingham Heart Study, Framingham, MA (C.A., A.L., M.G.L., E.J.B., J.M.M., S.J.B., R.S.V.) Department of Mathematics and Statistics, Boston University, Boston, MA (A.L., M.G.L.)
| | - Nicole L Spartano
- Department of Epidemiology, Boston University School of Public Health, Boston, MA (C.A., N.L.S., E.J.B., J.M.M., R.S.V.) The Whitaker Cardiovascular Institute, Boston University School of Medicine, Boston, MA (N.L.S., J.A.V., N.M.H.)
| | - Joseph A Vita
- The Whitaker Cardiovascular Institute, Boston University School of Medicine, Boston, MA (N.L.S., J.A.V., N.M.H.)
| | - Emelia J Benjamin
- Framingham Heart Study, Framingham, MA (C.A., A.L., M.G.L., E.J.B., J.M.M., S.J.B., R.S.V.) Department of Epidemiology, Boston University School of Public Health, Boston, MA (C.A., N.L.S., E.J.B., J.M.M., R.S.V.) Sections of Preventive Medicine and Cardiology, Department of Medicine, Boston University School of Medicine, Boston, MA (E.J.B., R.S.V.)
| | - Joanne M Murabito
- Framingham Heart Study, Framingham, MA (C.A., A.L., M.G.L., E.J.B., J.M.M., S.J.B., R.S.V.) Department of Epidemiology, Boston University School of Public Health, Boston, MA (C.A., N.L.S., E.J.B., J.M.M., R.S.V.)
| | - Dale W Esliger
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, United Kingdom (D.W.E.)
| | - Susan J Blease
- Framingham Heart Study, Framingham, MA (C.A., A.L., M.G.L., E.J.B., J.M.M., S.J.B., R.S.V.)
| | - Naomi M Hamburg
- The Whitaker Cardiovascular Institute, Boston University School of Medicine, Boston, MA (N.L.S., J.A.V., N.M.H.)
| | | | - Ramachandran S Vasan
- Framingham Heart Study, Framingham, MA (C.A., A.L., M.G.L., E.J.B., J.M.M., S.J.B., R.S.V.) Department of Epidemiology, Boston University School of Public Health, Boston, MA (C.A., N.L.S., E.J.B., J.M.M., R.S.V.) Sections of Preventive Medicine and Cardiology, Department of Medicine, Boston University School of Medicine, Boston, MA (E.J.B., R.S.V.)
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Spartano NL, Lamon-Fava S, Matthan NR, Ronxhi J, Greenberg AS, Obin MS, Lichtenstein AH. Regulation of ATP-binding cassette transporters and cholesterol efflux by glucose in primary human monocytes and murine bone marrow-derived macrophages. Exp Clin Endocrinol Diabetes 2014; 122:463-8. [PMID: 24838154 DOI: 10.1055/s-0034-1374600] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Individuals with type 2 diabetes mellitus are at increased risk of developing atherosclerosis. This may be partially attributable to suppression of macrophage ATP-binding cassette (ABC) transporter mediated cholesterol efflux by sustained elevated blood glucose concentrations. 2 models were used to assess this potential relationship: human monocytes/leukocytes and murine bone marrow-derived macrophages (BMDM).10 subjects (4 F/6 M, 50-85 years, BMI 25-35 kg/m²) underwent an oral glucose challenge. Baseline and 1- and 2-h post-challenge ABC-transporter mRNA expression was determined in monocytes, leukocytes and peripheral blood mononuclear cells (PBMC). In a separate study, murine-BMDM were exposed to 5 mmol/L D-glucose (control) or additional 20 mmol/L D- or L-glucose and 25 ug/mL oxidized low density lipoprotein (oxLDL). High density lipoprotein (HDL)-mediated cholesterol efflux and ABC-transporter (ABCA1 and ABCG1) expression were determined.Baseline ABCA1and ABCG1 expression was lower (>50%) in human monocytes and PBMC than leukocytes (p<0.05). 1 h post-challenge leukocyte ABCA1 and ABCG1 expression increased by 37% and 30%, respectively (p<0.05), and began to return to baseline thereafter. There was no significant change in monocyte ABC-transporter expression. In murine BMDM, higher glucose concentrations suppressed HDL-mediated cholesterol efflux (10%; p<0.01) without significantly affecting ABCA1 and ABCG1 expression. Data demonstrate that leukocytes are not a reliable indicator of monocyte ABC-transporter expression.Human monocyte ABC-transporter gene expression was unresponsive to a glucose challenge. Correspondingly, in BMDM, hyperglycemia attenuated macrophage cholesterol efflux in the absence of altered ABC-transporter expression, suggesting that hyperglycemia, per se, suppresses cholesterol transporter activity. This glucose-related impairment in cholesterol efflux may potentially contribute to diabetes-associated atherosclerosis.
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Affiliation(s)
- N L Spartano
- Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
| | - S Lamon-Fava
- Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
| | - N R Matthan
- Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
| | - J Ronxhi
- Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
| | - A S Greenberg
- Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
| | - M S Obin
- Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
| | - A H Lichtenstein
- Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
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Heffernan KS, Spartano NL, Lefferts WK, Augustine JA, Hughes WE, Gump BB. Arterial Stiffness and Pressure from Wave Reflections during Cognitive Challenge in Children and Adults. Med Sci Sports Exerc 2014. [DOI: 10.1249/01.mss.0000493822.93475.63] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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Augustine JA, Lefferts WK, Martin ED, Spartano NL, Heffernan KS. Vascular Function in Exercise-Trained Females. Med Sci Sports Exerc 2014. [DOI: 10.1249/01.mss.0000494178.62367.e0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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