Relations Between BMI Trajectories and Habitual Physical Activity Measured by a Smartwatch in the Electronic Cohort of the Framingham Heart Study: Cohort Study.

BACKGROUND: The prevalence of obesity is rising. Most previous studies that examined the relations between BMI and physical activity (PA) measured BMI at a single timepoint. The association between BMI trajectories and habitual PA remains unclear. OBJECTIVE: This study assesses the relations between BMI trajectories and habitual step-based PA among participants enrolled in the electronic cohort of the Framingham Heart Study (eFHS). METHODS: We used a semiparametric group-based modeling to identify BMI trajectories from eFHS participants who attended research examinations at the Framingham Research Center over 14 years. Daily steps were recorded from the smartwatch provided at examination 3. We excluded participants with <30 days or <5 hours of smartwatch wear data. We used generalized linear models to examine the association between BMI trajectories and daily step counts. RESULTS: We identified 3 trajectory groups for the 837 eFHS participants (mean age 53 years; 57.8% [484/837] female). Group 1 included 292 participants whose BMI was stable (slope 0.005; P=.75), group 2 included 468 participants whose BMI increased slightly (slope 0.123; P<.001), and group 3 included 77 participants whose BMI increased greatly (slope 0.318; P<.001). The median follow-up period for step count was 516 days. Adjusting for age, sex, wear time, and cohort, participants in groups 2 and 3 took 422 (95% CI -823 to -21) and 1437 (95% CI -2084 to -790) fewer average daily steps, compared with participants in group 1. After adjusting for metabolic and social risk factors, group 2 took 382 (95% CI -773 to 10) and group 3 took 1120 (95% CI -1766 to -475) fewer steps, compared with group 1. CONCLUSIONS: In this community-based eFHS, participants whose BMI trajectory increased greatly over time took significantly fewer steps, compared with participants with stable BMI trajectories. Our findings suggest that greater weight gain may correlate with lower levels of step-based physical activity.

Comparison of Daily Routines Between Middle-aged and Older Participants With and Those Without Diabetes in the Electronic Framingham Heart Study: Cohort Study.

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.

Association of Habitual Physical Activity With Home Blood Pressure in the Electronic Framingham Heart Study (eFHS): Cross-sectional Study.

BACKGROUND: When studied in community-based samples, the association of physical activity with blood pressure (BP) remains controversial and is perhaps dependent on the intensity of physical activity. Prior studies have not explored the association of smartwatch-measured physical activity with home BP. OBJECTIVE: We aimed to study the association of habitual physical activity with home BP. METHODS: Consenting electronic Framingham Heart Study (eFHS) participants were provided with a study smartwatch (Apple Watch Series 0) and Bluetooth-enabled home BP cuff. Participants were instructed to wear the watch daily and transmit BP values weekly. We measured habitual physical activity as the average daily step count determined by the smartwatch. We estimated the cross-sectional association between physical activity and average home BP using linear mixed effects models adjusting for age, sex, wear time, antihypertensive drug use, and familial structure. RESULTS: We studied 660 eFHS participants (mean age 53 years, SD 9 years; 387 [58.6%] women; 602 [91.2%] White) who wore the smartwatch 5 or more hours per day for 30 or more days and transmitted three or more BP readings. The mean daily step count was 7595 (SD 2718). The mean home systolic and diastolic BP (mmHg) were 122 (SD 12) and 76 (SD 8). Every 1000 increase in the step count was associated with a 0.49 mmHg lower home systolic BP (P=.004) and 0.36 mmHg lower home diastolic BP (P=.003). The association, however, was attenuated and became statistically nonsignificant with further adjustment for BMI. CONCLUSIONS: In this community-based sample of adults, higher daily habitual physical activity measured by a smartwatch was associated with a moderate, but statistically significant, reduction in home BP. Differences in BMI among study participants accounted for the majority of the observed association.

Adherence of Mobile App-Based Surveys and Comparison With Traditional Surveys: eCohort Study.

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.

Association of Habitual Physical Activity With Cardiovascular Disease Risk.

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.

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.

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.

Design and Preliminary Findings From a New Electronic Cohort Embedded in the Framingham Heart Study.

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.

Effect of a Game-Based Intervention Designed to Enhance Social Incentives to Increase Physical Activity Among Families: The BE FIT Randomized Clinical Trial.

Importance: Gamification, the application of game design elements such as points and levels in nongame contexts, is often used in digital health interventions, but evidence on its effectiveness is limited. Objective: To test the effectiveness of a gamification intervention designed using insights from behavioral economics to enhance social incentives within families to increase physical activity. Design, Setting, and Participants: The Behavioral Economics Framingham Incentive Trial (BE FIT) was a randomized clinical trial with a 12-week intervention period and a 12-week follow-up period. The investigation was a community-based study between December 7, 2015, and August 14, 2016. Participants in the modified intent-to-treat analysis were adults enrolled in the Framingham Heart Study, a long-standing cohort of families. Interventions: All participants tracked daily step counts using a wearable device or a smartphone, established a baseline, selected a step goal increase, and received daily individual feedback on goal performance by text message or email for 24 weeks. Families in the gamification arm could earn points and progress through levels based on physical activity goal achievement during the 12-week intervention. The game design was meant to enhance collaboration, accountability, and peer support. Main Outcomes and Measures: The primary outcome was the proportion of participant-days that step goals were achieved during the intervention period. Secondary outcomes included the proportion of participant-days that step goals were achieved during the follow-up period and the change in the mean daily steps during the intervention and follow-up periods. Results: Among 200 adults comprising 94 families, the mean age was 55.4 years, and 56.0% (n = 112) were female. During the intervention period, participants in the gamification arm achieved step goals on a significantly greater proportion of participant-days (0.53 vs 0.32; adjusted difference, 0.27; 95% CI, 0.20-0.33; P < .001) and had a significantly greater increase in the mean daily steps compared with baseline (1661 vs 636; adjusted difference, 953; 95% CI, 505-1401; P < .001) than the control arm. During the follow-up period, physical activity in the gamification arm declined but remained significantly greater than that in the control arm for the proportion of participant-days achieving step goals (0.44 vs 0.33; adjusted difference, 0.12; 95% CI, 0.05-0.19; P < .001) and the mean daily steps compared with baseline (1385 vs 798; adjusted difference, 494; 95% CI, 170-818; P < .01). Conclusions and Relevance: Gamification designed to leverage insights from behavioral economics to enhance social incentives significantly increased physical activity among families in the community. Trial Registration: clinicaltrials.gov Identifier: NCT02531763.

Risk factor differences in calcified and noncalcified aortic plaque: the Framingham Heart Study.

OBJECTIVE: The objective of this study was to determine the prevalence and risk factor (RF) correlates of aortic plaque (AP) detected by cardiovascular magnetic resonance (CMR), which mainly shows noncalcified plaques, and by noncontrast computed tomography (CT), which best depicts calcified plaques, in community-dwelling adults. APPROACH AND RESULTS: A total of 1016 Framingham Heart Study Offspring cohort members (64 ± 9 years; 474 men) underwent CMR and CT of the aorta. Potential RFs for AP (age; sex; body mass index; blood pressure; low-density lipoprotein and high-density lipoprotein cholesterol; fasting glucose; C-reactive protein; prevalent hypertension, diabetes mellitus, smoking; use of antihypertensive, diabetes mellitus, or lipid-lowering drugs) were compared between participants, with zero versus nonzero AP by CMR and by CT. Candidate RFs attaining P<0.05 for difference with either imaging modality were entered into multivariable logistic regression models adjusting for age, sex, and other RFs. Odds ratios were calculated for modality-specific prevalence of AP. Associations between RFs and continuous measures of AP were assessed using Tobit regression. Prevalence of CMR and CT AP was 49% and 82%, respectively. AP burdens by CMR and CT were correlated, r=0.28, P<0.0001. Increasing age and smoking were associated with prevalent AP by both CMR and CT. Additionally, prevalent AP by CMR was associated with female sex and fasting glucose and prevalent AP by CT with hypertension treatment and adverse lipid profile. CONCLUSIONS: AP by CMR and CT are both associated with smoking and increasing age, but other RFs differ between calcified and noncalcified AP. The relative predictive value of AP detected by CMR versus by CT for incident cardiovascular events remains to be determined.

Renal artery calcium, cardiovascular risk factors, and indexes of renal function.

Vascular calcium is well studied in the coronary and peripheral arteries, although there are limited data focusing on calcium deposits specific to renal arteries. The associations among renal artery calcium (RAC), cardiovascular disease risk factors, and indexes of renal function are unknown. We examined 2,699 Framingham Heart Study participants who were part of a multidetector computed tomography substudy from 2008 to 2011. RAC was measured as a calcified plaque of >130 HU and an area of >3 contiguous pixels. Detectable RAC was defined as an Agatston score >0. Chronic kidney disease was defined as an estimated glomerular filtration rate of <60 ml/min/1.73 m(2). Microalbuminuria was defined as an albumin/creatinine ratio of ≥17 mg/g for men and ≥25 mg/g for women. Multivariable adjusted logistic regression models were used to evaluate the associations between RAC, cardiovascular disease risk factors, and renal function. The associations were secondarily adjusted for coronary artery calcium (CAC) that was used as a marker of nonrenal systemic vascular calcium. The prevalence of RAC was 28.2%; this was similar in women (28.8%) and men (27.5%). Patients with RAC had a higher odds of microalbuminuria (odds ratio [OR] 1.79, 95% confidence interval [CI] 1.22 to 2.61, p = 0.003), hypertension (OR 2.11, 95% CI 1.69 to 2.64, p <0.001), and diabetes (OR 1.60, 95% CI 1.14 to 2.24, p = 0.01) but not chronic kidney disease (OR 0.87, 95% CI 0.58 to 1.32). After adjustment for CAC, the association with microalbuminuria and hypertension persisted, but the association with diabetes became nonsignificant. In conclusion, RAC is common and independently associated with microalbuminuria and hypertension after adjustment for nonrenal vascular calcium. RAC may be uniquely associated with these markers of renal end-organ damage.

Distribution of abdominal aortic calcium by computed tomography: impact of analysis method on quantitative calcium score.

RATIONALE AND OBJECTIVES: Abdominal aortic calcification (AAC) can be quantified using computed tomography (CT), but imaging planes are prescribed based on bony landmarks, so that individual variation between the landmark and the aortoiliac junction can result in variable aortic coverage. In the Framingham CT substudy, we scanned a 15-cm (Z-direction) abdominal segment cranial to the S1 vertebral body. We sought to determine the range and distribution of length of aorta scanned and the distribution of AAC within the abdominal aorta and to compare burden of AAC measured from fixed-length segments versus AAC from all slices cranial to the aortoiliac bifurcation. MATERIALS AND METHODS: AAC was quantified by modified Agatston score (AS) in 100 Framingham Heart Study participants (60 ± 13 years old, 51 men). We compared the AS measured from 5-cm and 8-cm segments with the ASALL (total visualized aorta). RESULTS: Of 100, 73 participants had AAC >0. The total length of aorta imaged was ≥8 cm in 84% of participants. Qualitatively, 5-cm and 8-cm segments correctly identified 96% and 99%, respectively, of participants as having or not having AAC. Quantitatively, AS8cm was within 20% of ASALL in four-fifths and within 30% of ASALL in nine-tenths of participants. AS5cm more severely underestimated ASALL. CONCLUSION: The use of S1 as the caudal imaging landmark in a 15-cm slab yields ≥8 cm aortic coverage in most adults. Both 5-cm and 8-cm analysis strategies are comparable to analyzing the total visualized abdominal aorta for prevalent AAC, but only 8-cm segment analysis yields quantitatively similar measures of AAC.

Prevalence and distribution of abdominal aortic calcium by gender and age group in a community-based cohort (from the Framingham Heart Study).

Abdominal aortic calcium (AAC) is associated with incident cardiovascular disease. However, the age- and gender-related distribution of AAC in a community-dwelling population free of standard cardiovascular disease risk factors has not been described. A total of 3,285 participants (aged 50.2 ± 9.9 years) in the Framingham Heart Study Offspring and Third Generation cohorts underwent abdominal multidetector computed tomography from 1998 to 2005. The presence and amount of AAC was quantified (Agatston score) by an experienced reader using standardized criteria. A healthy referent subsample (n = 1,656, 803 men) free of hypertension, hyperlipidemia, diabetes, obesity, and smoking was identified, and participants were stratified by gender and age (<45, 45 to 54, 55 to 64, 65 to 74, and ≥75 years). The prevalence and burden of AAC increased monotonically and supra-linearly with age in both genders but was greater in men than in women in each age group. For those <45 years old, <16% of the referent subsample participants had any quantifiable AAC. However, for those >65 years old, nearly 90% of the referent participants had >0 AAC. Across the entire study sample, AAC prevalence and burden similarly increased with greater age. Defining the 90th percentile of the referent group AAC as "high," the prevalence of high AAC was 19% for each gender in the overall study sample. The AAC also increased across categories of 10-year coronary heart disease risk, as calculated using the Framingham Risk Score, in the entire study sample. We found AAC to be widely prevalent, with the burden of AAC associated with 10-year coronary risk, in a white, free-living adult cohort.

Parental occurrence of premature cardiovascular disease predicts increased coronary artery and abdominal aortic calcification in the Framingham Offspring and Third Generation cohorts.

BACKGROUND: Parental premature cardiovascular disease (CVD) is a risk factor for coronary heart disease (CHD). We related validated parental premature CVD with the subclinical measures of coronary artery (CAC) and abdominal aortic (AAC) calcification in the community. METHODS AND RESULTS: We studied 2 generations of Framingham Heart Study subjects who underwent multidetector computed tomography measurements of CAC and AAC and who had 2 parents in the study. Subjects included 797 Framingham Offspring (mean age, 63 years; 56% women) and 1238 Third Generation (Gen3) (mean age, 46 years; 47% women) participants free of CVD. Generalized estimating equations adjusted for major CVD risk factors were used to relate validated parental premature CVD and CHD to CAC and AAC, defined by >90th percentile age- and sex-specific cut points from a healthy subsample. Parental premature CVD was associated with CAC among Gen3 (odds ratio=2.17 [1.41 to 3.33]; P<0.001) and nonsignificantly among Offspring (odds ratio=1.42 [0.91 to 2.22]; P=0.12). Parental premature CHD was associated with CAC among Gen3 (odds ratio=2.22 [1.22 to 4.01]) but not Offspring. Parental premature CVD was not associated with AAC in either cohort. Parental premature CHD was associated with AAC among Gen3 (odds ratio=1.65 [0.99 to 2.75]; P=0.05) but not among Offspring. The magnitude of risk conferred was greater for paternal than maternal premature CVD. CONCLUSIONS: Parental premature CVD is associated with CAC, and premature CHD is associated with AAC, after adjustment for risk factors, particularly in younger middle-aged adults. Risk conferred by parental premature CVD on vascular calcification may be mediated through novel mechanisms not accounted for by classic CVD risk factors known to cause atherosclerosis.