JMIR Publications

ABSTRACT

FEASible is a cross-sectional observational study that explores women’s daily living patterns through wearable devices and home environment sensors to validate the use of physical activity and indoor air quality data as indicators of risk for metabolic syndrome (MetS) and cardiovascular disease (CVD; NHLBI, R01HL168374). Leveraging transdisciplinary expertise, we implement a low-cost, dense sampling approach among 800 adult women, 60% Hispanic/Latina, with a subgroup of 225 participants opting for neuroimaging to assess MetS-related brain vulnerability. Participants residing in Central Texas use a smartwatch and a custom-built air quality sensor to monitor their activities and environment for two weeks. Other variables, such as social determinants of health, medical history, and lifestyle, are reported through surveys. During their initial visit, we gather blood pressure measurements, body composition, and lipid profile information. 805 participants have completed the eligibility survey, from which 204 participants have completed two weeks of sensor data collection, showing a diverse participant pool comprising 60.3% Hispanic/Latinas, 38.8% non-Hispanic/Latinas, and 0.9% unknown. Participants were aged 18 – 40 years, with an average age of 27 ± 6 years. Moreover, we have established a feasible pipeline to collect data that will help yield valuable insights into MetS risk factors among Latina women, including brain scan magnetic resonance imaging (MRI) data and environmental exposure measurements. This paper aims to provide a rationale for procedures and case examples from the first year of data collection leading to predictive health risk modeling, thus informing future interventions on MetS, heart disease, and all-cause mortality among Latina women.