Social Determinants of Health: Insights from Location Big Data

Abstract

Rocketing hospitalization rates and costs call for a deeper understanding of the connection between health outcomes and individuals' social determinants of health, such as lifestyle and socio-economics. Such knowledge holds important implications for health marketing, policymaking, and policy communication. Building on the literature that has focused on either lifestyle identification or the association between health outcomes and limited behavioral features derived from small samples, we propose a novel framework leveraging the population-scale location data that capture granular individual behavior 24/7. This framework integrates unsupervised topic models and sequential deep learning models to characterize individual lifestyles and quantify their association with future hospitalizations while integrating other social determinants of health. Applied to 45 million location records from a major metropolitan region in the U.S., the framework successfully uncovers heterogeneous lifestyles. Several key findings then emerge. An individual's lifestyle choice turns out to be a more critical predictor of future hospitalization than his/her socio-economic factors or accessibility to healthcare facilities. Lower-income populations can present healthy lifestyles, while high-income populations can present unhealthy ones. Population with lower accessibility to healthcare or facilities can present healthy lifestyles; while a population with higher accessibility can present unhealthy ones. Individuals with busy, varying work routines and limited gym visits are 2.01 times likely to be hospitalized within a year, compared to the population average. Importantly, regularity, rather than total time spent, toward healthy or unhealthy activities, predict future hospitalization. Overall, an individual's lifestyle choice is more critical than the socio-economic, accessibility, and their community factors, consistent with a recent review on social determinants in EHR.