This browser explores health in Los Angeles within a biobank collected at the UCLA Health System. The data is apart of the UCLA ATLAS Community Health Initiative and the UCLA Clinical Neurogenomics Research Center. We explore several aspects of health that may be of interest to researchers and community members, particularly those who have an interest in studying health disparities. This research is published in Caggiano et al., 2023, Nature Medicine.

We identified clusters of related individuals using an unsupervised machine learning approach and genotyping data. This found hundreds of clusters of patients, representing many understudied groups in the context of Southern California. Here, we focus on the 21 largest clusters, representing 97% of our sample.

We then explore how each cluster interacts with the health system. For this analysis, we considered what diagnoses, in the form of PheCodes, were more likley to be received by a cluster, and what medical specialties the cluster was more or less likely to visit. We also examined whether there were Los Angeles zipcodes where members of a cluster were more likely to visit a doctor's office. Lastly, we examined properties of genetic sharing within the cluster, something that might be useful for researchers seeking to learn about genetic risk for disease.

Note: These results are only correlations. They do not indicate that cluster membership or genetics is the cause of the results reported here.

Health is a complex phenomenon that is strongly influenced by structural factors like the environment, socioeconomic status, race, sex, diasbility and other and sociocultural factors. The explicit goal of this research is to provide opportunities to identity differences in health outcomes within the UCLA Health System. Please see our FAQ page for a full discussion of what these results do or do not mean.