Traditional epidemiology cohorts have contributed greatly to our understanding of CVD and its risk factors, but
concerns have been raised about their resource intensive nature, as well as their failure to integrate data from
outside the research center. Digital and mobile health (mHealth) technologies provide data on individuals’
behaviors, risk factors, and CVD events. The growing ubiquity of mHealth solutions provides an unprecedented
opportunity to add novel “real world” cardiovascular phenotypes to cohort studies. MHealth may facilitate more
frequent, convenient, and meaningful interactions with cohort participants. Despite the availability of myriad
devices, few systems have been designed to facilitate long-term cardiovascular phenotyping and CVD
surveillance. We propose to enhance the FHS-NExT (Framingham Heart Study-Novel Examination using
Technology) system, which includes a custom smartphone application (app) and data from a smartwatch
(heart rate/steps) and digital blood pressure (BP) cuff, for use by FHS Generation 3 (Gen3) and multi-ethnic
Omni 2 participants. We will identify factors associated with long-term adherence, and relations between
mHealth and digital phenotypes with validated measures of fitness and arterial stiffness. Specific aims:
Aim 1. Enhance the FHS-NExT smartphone app to promote adherence and compare the new FHS-NExT
app CVD risk factor surveys against conventional measures in the FHS Research Center. We will
enhance the FHS-NExT app, add new messaging and interactive capabilities to facilitate long-term use of the
FHS-NExT app (n=2250), smartwatch (n=1500), and BP device (n=1500) and correlate FHS CVD risk score as
assessed using the app to the FHS CVD risk score from the research center exam.
Aim 2. Identify factors associated with successful long-term use of the FHS-NExT system, including
the app, smartwatch, and digital BP device. System adherence will be defined based on: 1) app completion
of lifestyle and CVD risk factor surveys every 3 months (n=2250); 2) donning the smartwatch and recording
=1000 steps daily (n=1500); and 3) taking BP measures =once weekly (n=1500). We will identify participant or
system-related factors, that affect adherence to the FHS-NExT system (n=1500 participants) over 12 months.
Aim 3. Examine relations of novel exercise capacity measures by cardiopulmonary exercise testing
(CPET) with average resting HR and daily step counts from smartwatch recordings over 30 days.
Aim 4. Examine relations of arterial stiffness by tonometry with mean weekly BP and mean BP
variability over 6 months.
We bring together a highly productive, multi-disciplinary team with expertise in app development, mHealth and
digital research methods and analysis, “big data” integration, behavioral science, & CVD epidemiology. We
propose to build new, scalable capabilities for digital and mHealth data collection, and test the relations between
traditional in-clinic measures of cardiovascular fitness and arterial tonometry and novel mHealth phenotypes.