R Shiny User Application

In the first tab of the Shiny application, users may explore possible relationships between breast cancer variables and other variables of interest, such as demographics or individual health characteristics. Users are prompted to select a breast cancer variable of interest: mammography use or breast cancer mortality. Then, the user may select a second variable from a drop-down menu of demographic and individual health characteristics, such as racial/ethnic diversity, high school completion in the population, obesity prevalence, and so on. The application will output a scatterplot that allows the user to easily visualize any trends between the two variables selected. As an added feature, the user may select any datapoint and receive information about that datapoint, including which city it represents and the point estimates for the selected variable, in a table above the plot.

Also in the first tab of the Shiny application, users may observe trends between racial/ethnic groups for a selection of demographic and individual-health characteristics. Two options are available to visualize the data by race/ethnicity. In the first section, users may select one variable and the application will output a violin plot of the data stratified by racial/ethnic group. In the second section, users may select a variable, and the application will produce a scatterplot of this variable correlated with breast cancer mortality, stratified by racial/ethnic group. These features allow users to clearly visualize trends in demographic and individual health characteristics between racial/ethnic groups, interpret how these trends may impact breast cancer mortality, and interpolate how these trends may impact breast cancer care overall.

In the second tab of the Shiny application, users are able to visualize the trends in breast cancer screening and mortality in each of the 500 cities by the number of facilities offering mammography services in those cities and gain a national perspective of these relationships. This tab features an output plot of the United States with points for each of the 500 cities in the 500 Cities Project. The size of the point for each city is indicative of the number of facilities offering mammography services in that city (per 100,000 persons), with the larger points indicating a larger ratio of facilities in that city. Users may select either of the breast cancer variables provided (mammography use or mortality), and the points will be color-coded based on a continuous scale of the selected variable. This allows users to easily visualize the relationship between the number of facilities offering mammographic services and a breast cancer outcome variable of interest. In addition, users can visualize any spatial trends across the nation. As a second option, users are able to select ~10 cities to make similar comparisons as the larger national perspective, and the users will be provided with a table of the values of the selected variable for the cities they selected.

In the third tab of the Shiny application, users are able to select a variable of interest (e.g., mammography use, racial/ethnic diversity) to produce a heat map displaying the distribution of the user-selected variable across New York City census tracts. Understanding the trends of these demographic and individual health characteristics is important in fully contextualizing the trends seen in any infectious or chronic disease, and in the context of this project, a spatial understanding of these trends within New York City will allow users to further contextualize the breast cancer mortality overall of the city as well as mammography use broken down by census tracts.

This clip features a mock use of the R Shiny application. Click on the video to watch it on Youtube!