Mia & Kylie Project

Suicide Rates by Race, Sex, and Age in the United States

Kylie Fuerbacher and Mia Simon

By analyzing the suicide rates based on race, sex, and age throughout the years we can try to understand where the critical points in the data are.

Mental health awareness is extremely important. Mostly everyone either knows or knows of someone who has struggled with suicidal thoughts, so it is not an issue to take lightly. In this project, we used a data file containing data from 1980 to 2017 about the suicide rates based on the categories of race, sex, and age and visualized them into graphs to gain clearer insights.

Below is a general graph showing a basic trendline for the suicide rates out of 100,000 people every year for all persons in the dataset.
All of the suicide rates in this dataset are out of 100,000 people. When considered in the scope of the population of the United States, which is over 300 million, these numbers are actually quite high.

As you can see, the data is different for each year.

Click the buttons below to see the data for the corresponding year.

1980 2008 2017

After considering the general trendline and data for each years separately, we show race, sex, and age animated through the years for a more direct comparison.
The bars decrease slightly around the middle of the timeframe (1998-2003) then slightly increase toward the end. Caucasians consistently have the highest suicide rates, followed by Native American/Alaskan Natives, and then it alternates between Blacks/African Americans and Asians/Pacific Islanders.
The bars decrease slightly around the middle of the timeframe (1998-2003) then slightly increase toward the end. Males consistently have the highest suicide rates by a significant factor.
The bars decrease slightly around the middle of the timeframe (1998-2003) then slightly increase toward the end. Ages 75-84 had the highest rate until about 2004 when it fluctuated with ages 45-54, then ages 35-44 and 54-64 also surpassed it. In the end, 45-54 is the highest followed 54-64 and an approximate tie between 25-34, 35-44, and 75-84.
After reviewing these categories, we combined some of them to take a step further into the data.
Before, we could see that males and females have different rates, but now in the above graph we see that males and females follow different trends within each race. For example, Black males have a higher rate that Asian males, but it is the opposite for Black and Asian females. There is more overlap with the females becuase the rates are more closely related while the males have a larger spread. Females follow a more general trendline compared to the males where there is more increase and decrease.
Now in the above graph we see that males and females follow different trends within each age range. Agian, there is more overlap with the females becuase the rates are more closely related while the males have a larger spread. Females follow a more general trendline compared to the males where there is more increase and decrease.