Leading Causes of Death in the United States

Charts & Graphs, Visualization


When I researched the topic: leading causes of death in data visualization, I found most of the people who do this topic are more focus on showing the high percentage of heart disease and put more focus on it.

Age-adjusted death rates for the 10 leading causes of death: United States, 2016 and 2017

However, I am interested in suicide which is the lowest rate of disease. Other diseases have many irresistible factors, but suicide is a spontaneous behavior. I want to know more about suicide and lots of questions came to my mind

  • Has suicide been the lowest cause of death from pass to now?
  • Has the suicide rate increased or decreased in recent years?
  • Which state has the highest suicide rate?



This an example I found about this topic. The death rate data visualization let me think about it could be interesting if I create a map which answers the question that does geography have an impact on suicide rate? Using the map to visualization this data can show the relationship between suicide rate and geography clearly. People can understand it in 1 second. In this example, it also shows the age-adjusted death rate in line graphics. Line graphics has the advantages of showing the change over time and it is the perfect form to let people find the answer to the question: Has the suicide rate increased or decreased in recent years?

For me, the bar charts in this example are not good for they used to many colors without any meanings. It is the part I think can be simplified l I designed my visualization.

Design Methodology and procedures 


Openrefine: http://openrefine.org/ Help me cleaning the messy data.

Tableau Public:https://public.tableau.com/en-us/s/ Tools to visualize your data


Data Dov:I found the basic data of Leading Causes of Death_United States in data.gov

The original data I used: https://catalog.data.gov/dataset/age-adjusted-death-rates-for-the-top-10-leading-causes-of-death-united-states-2013

After I used Openrefine to clean the unnecessary data in the original file, the first thing I would like to do is to refine the data visualization of Leading Causes of Death: United States.


In this visualization, I emphasize the low rate of suicide with blue. The other unrelated elements all use grey. People can find the answer very fast that suicide is the lowest rate in this visualization.

To answer the question “has the suicide rate increased or decreased in recent years?” and “Has suicide been the lowest cause of death from pass to now?” I created two visualizations.


In this line graphics, we can clearly see that suicide is keeping the lowest rate since 1999 to 2016. But if we change the line graphics to area chart and only see the data of suicide, we can find that the suicide rate is keeping increasing. And the suicide rate is growing very fast.


The most interesting finding in this project is that when I combine the geography and suicide rate People can see that the rate are higher in the coastal city.


According to this map, Viewers can see that the top three suicide area is California Texas and Florida. The purpose of this graphic is showing the top 10 high suicide are in the United States and people can find and understand it easily.


Suicide is the lowest rate in all categories, I want my graphics could let people pay attention to it. The reason is that people care about mental illness and pay more attention to people who have this issue in recent years, however, the rate of suicide is still accelerating. I feel that there is room for improvement in the map graphics. Because the suicide rate in a place has the problem that it is impacted by the total population in that space. I think I should find more data about suicide in a different area when I make similar graphics next time so that my chart reliability and authenticity can become higher.

Additionally, I think it could be interesting if I visualize all the diseases in the geography map. Putting them together may create some new findings of which area has a higher rate of different diseases.