The data used this week is Health Data that was collected from Social Explorer. The data will be focusing on the number of preventable deaths for individuals who died prematurely for nothing having health insurance. The data will be presented visually on the national level and then draw comparison between two states (North Carolina & New York).
tm_shape(am, projection = 2163) + tm_polygons("Preventable.Deaths", palette = "-RdBu", midpoint = 50) + tm_shape(us) +
tm_borders(lwd = .6, col = "white", alpha = 1) + tm_layout(title = "US Preventable Medical Deaths", title.position = c("center", "top"),
legend.position = c("left", "bottom"), legend.text.size = .5, frame = TRUE)
By looking at the national visualization of preventable medical death, we can observe that the states with the largest number of preventable medical deaths are mainly located on the West Coast of the US. This can be attributed to the fact that the counties located on on the West Coast are larger when compared to the rest of the nation. Further observation also indicatred that the mid-western states have the higher count of missing data regarding preventable medical deaths.
ny <- map %>%
filter(STATEFP == 36)
tm_shape(ny, projection = 2163) + tm_polygons("Preventable.Deaths", palette = "-RdBu", midpoint = 50, border.col = "white") +
tm_text("NAME", size = .3) + tm_layout(title = "NY Preventable Medical Deaths", title.position = c("center", "top"),
legend.position = c("left", "center"), legend.text.size = .5, frame = TRUE)
Upon observing New York State, we can generally state that NY has a low count of preventable medical deaths. Broken down by county, it would seem that queens county has the highest count of preventable medical deaths. Further analysis also seems to indicate that the number of preventable medical deaths is higher when counties located near the NYC area.
nc <- map %>%
filter(STATEFP == 37)
tm_shape(nc, projection = 2163) + tm_polygons("Preventable.Deaths", palette = "-RdBu", midpoint = 50, border.col = "white") +
tm_text("NAME", size = .5) + tm_layout(title = "NC Preventable Medical Deaths", title.position = c("center", "top"),
legend.position = c("left", "center"), legend.text.size = .5, frame = TRUE)
Now, when analyzing North Carolina, we can see that the number of preventable medical deaths is much higher when compared to NY. Upon further analysis, we can state that a the center of the state seems to have the highest number of preventable medical deaths as opposed to the outer counties.
A brief assumption of why North Carolina has higher preventable medical deaths than New York could amount to the accessibility to afforable haealth insurance and overall urbanization. Where NY can be considered to be more urbanized than NC, this would mean there would be more accessibility to healthcare providers when compared to the vast amount of space/open land in NC. In reference to the healthcare system, NY has more available options to health insurance.
preventable
Between Spatial and Non-Spatial approaches, the non-spatial approach is a more simiplifed apprach for reading the data. From this approach, you can easily draw the conclusion that the three states with the highest number of prevenetable medical deaths are:
However, the Spatial apprach would provide research a much more detailed look at which counties are the highest risk for having the highest count of preventable medical deaths. It also provides the insight for which counties would require more data in order to obtain a much more representative visualization of at risk counties.
countymap2 <- counties(cb = FALSE)
options(tigris_class = "sf")
tm_shape(ny2, projection = 2163) + tm_polygons("Preventable.Deaths2", palette = "-RdBu", midpoint = 50, border.col = "white") +
tm_text("NAME", size = .3) + tm_layout(title = "NY Preventable Medical Deaths", title.position = c("center", "top"),
legend.position = c("left", "center"), legend.text.size = .5, frame = TRUE)
Upon running the cd=FALSE command, there wasn’t much difference in terms of speed. However, the difference did appear in the visualization for the state if New York. Where the visual shown above presents a more detail state view of NY, this variation shows minor differences in the outline of the state (most notably in the way that Long Island looks). Another area where a difference can be spotted is on Jefferson and Oswega counties where the land seems to extend a bit into where the lakes would be located.