Data Visualization on the Leading causes of death in U.S.

Posted on Dec 25, 2018
The skills the author demoed here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.


The life expectancy in the U.S. has been rising over the past century, owing to the tremendous strides made in biomedical research and in health care management. Over the past few decades, data shows there is a steady decline in death from the leading causes but U.S. death rate rose for the third straight year. Americans are dying in different ways than they used to. The United States currently ranks highest in health care spending among the developed nations in the world, yet U.S. sees higher mortality than almost every other developed country.

Cardiovascular diseases remain the most common of death in the U.S. Nationwide the death rate from heart diseases decreased from 507 deaths for every 100,000 people in 1980 to 253 deaths for every 100,000 people in 2014. However, this does not appear to be the case in every part of the country. The local and regional variations in lifestyle, income and healthcare access are contributing to this disparity. Similar trend can be seen in other diseases as well.


To understand how much our location affects our health The Institute for Health Metrics and Evaluation gathered death records from the local jurisdictions and compiled data for all causes of death for the past 35 years. This dataset contains information for all causes of death, including the uncertainty ranges. The full dataset is available on the Institute website. This information aims to help individuals to visualize deaths by county and by year.


I created a shiny app that would allow users to view trends of 18 causes of death in United States and look at trends as they change over time. The two dropdown menus will help the user pick a death cause and a State. A slider will help the user pick a year from 1980 to 2014.

For visualization I used ggplot2 and for geospatial visualization I used maps library from R. Barplots allow the user to compare death rate measurements by county in a U.S. state and loine plots display the death rates in each state from 1980 to 2014.

Data Visualization on the Leading causes of death in U.S.

Interesting Data Findings:

The mortality rates in the U.S. by heart diseases, cancers, diarrhea & common infectious diseases and transport injuries are on a decline. The mortality rates by Diabetes, Mental and substance abuse are increasing.

Data Visualization on the Leading causes of death in U.S.


Data Visualization on the Leading causes of death in U.S. Deaths by HIV/AIDS and tuberculosis peaked in mid 1990s. Increase in public awareness and development of anti-retroviral drugs stemmed the death rates. There is a steady decline in death rates by HIV. Deaths by Forces of nature, war and legal intervention were very few for most part of the past years except for a brief period between 2001 and 2010. U.S. suffered from natural calamities such a Hurricane Katrina and its involved in armed conflicts overseas.


Conclusions and Future Directions:

My Rshiny app proved to a useful tool for visualizing and investigating the mortality rates by leading causes of death across the United States. Understanding clear regional patterns for various diseases and deaths will be very useful for both policy makers and health care providers to intervene and provide better health care. For a more robust and insightful app, I would like to include the death rates at the county level across the United States.

Click here for App

Click here for Code

About Author

Rajesh Arasada

Data scientist and cell biologist with >10 years of bio-medical research experience. Implemented Machine learning (ML) algorithms in R and Python to solve real-world problems.
View all posts by Rajesh Arasada >

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