  Social networks influence health-related behaviors, such as obesity and
smoking. While researchers have studied social networks as a driver for
diffusion of influences and behaviors, it is less understood how the structure
or topology of the network, in itself, impacts an individual's health behaviors
and wellness state. In this paper, we investigate whether the structure or
topology of a social network offers additional insight and predictability on an
individual's health and wellness. We develop a model called the Network-Driven
health predictor (NetCARE) that leverages features representative of social
network structure. Using a large longitudinal data set of students enrolled in
the NetHealth study at the University of Notre Dame, we show that the NetCARE
model improves the overall prediction performance over the baseline models --
that use demographics and physical attributes -- by 38%, 65%, 55%, and 54% for
the wellness states -- stress, happiness, positive attitude, and self-assessed
health -- considered in this paper.
