Urban neighborhood characteristics are vastly diverse and can help to explain social patterns and mental health outcomes. A granular examination of neighborhood sociodemographic factors and the patterns of mobility that are created by the residents within these areas can reveal influences on depression rates. The close ties between sociodemographic factors and neighborhood environmental characteristics, such as mobility, can serve as indicators for why some urban areas are more affected than others. Using data from the American Community Survey, as well as collected geolocational data and depression instances from Twitter users in Chicago and outlying areas, regression and spatial autocorrelational models were developed to determine sociodemographic factor effects on mobility and depression rate in urban neighborhoods. Analysis shows that the percent population of white individuals positively impacted the radius of gyration for a given area, while percent population Hispanic, higher level education, and a higher Gini wealth inequality index has a negative effect on radius of gyration. Models including mobility as an influencing factor of depression show that an increased radius of gyration has a significant effect on higher depression rates, while a higher Gini wealth inequality index also decreases depression rates. All variables were spatially significant, and areas that share similar sociodemographic, mobility, and depression patterns cluster in the city center as well as the outlying areas of Chicago. These findings can help illustrate which neighborhood characteristics should be closely examined when determining patterns of depression, as well as the identifying sociodemographic variables that can be monitored to help support areas with higher depression rates than others.
Kaylah Thomas (Wed,) studied this question.