PROJECT SUMMARY/ABSTRACT
Passive sensing of Latina women's daily living experience as proxy measures of health risk must be brought
to scale. We propose to validate the integrated measurements from Fitbits, smartphones, purpose-built
environmental sensors (Beacon), GPS, and a purpose-built smartphone app (Hornsense), to assess physical
activity, sleep, and environmental exposures as they relate to metabolic syndrome (MetS) and MetS-related
brain vulnerability. We will develop a pipeline to create and interpret networks signifying how MetS relate to brain
integrity in Latina women and identify which environmental factors contribute to increased risk for MetS.
To achieve these goals, we synergize expertise from multiple disciplines, advance pilot data, and ground-truth
novel integrated measures. First, it is essential to define how MetS risk manifests in this sample by identifying
how MetS affects brain integrity in a subsample of Latina women compared to white women (n=225) and
compare these methods to traditional clinical assessments of MetS (defined by AHA/NHLBI). Measures of
cerebral metabolism (N-acetyl aspartate, NAA, myo-inositol, mI and glutamate, Glu) will form a network of risk
and brain vulnerability. Daily living will be assessed in 1,000 women (60% Latina) through 30 days of dense
sensing in the home environment. Participants will wear Fitbit Inspire devices and have the Hornsense app on
their cell phones. Environmentally, we will validate the purpose-built Beacon, which measures environmental
factors of particulate matter (PM2.5,- allergens that influence air quality), nitrogen oxides (NOx - gases within
smog), carbon monoxide (CO) and carbon dioxide (CO2), temperature, relative humidity (RH), and amount of
noise, first against research-grade reference instruments in well-controlled sleep chambers and smart test
homes, and second in participant homes. During the dense sensing, Beacons and Personal Air Quality Monitor
(PAM) will be placed in the bedroom and outside the home for one month. The 24 hours of activity, location, and
all environmental values will be compared with MetS risk and MetS-related brain vulnerability because brain
integrity is among the earliest markers of vulnerability, representing a high risk for poor health outcomes and
quality of life in older age. Network analysis of these data will identify the critical central nodes of risk.
Scaling our pilot sensing protocols will determine the feasibility and efficacy of integrated measurements of
daily behavior, activity, sleep, and environmental attributes to predict MetS and MetS-related brain vulnerability
in Latina women. Identifying valid strategies for targeting individual behaviors and contexts is essential for future
prevention efforts to be designed with greater precision, particularly for Latina women.
