Abortion has been a talked about issue for quite some time now, even more so after “Roe v. Wade” was overturned this past June. This means that abortion is no longer a federal constitutional right. The issue of abortion is now up to each individual state. I am curious to see if there is a correlation between number of abortions per state and whether that state is overall republican or democratic. My hypothesis is that democratic states will have more abortions than republican states. I believe this because republicans are typically pro-life, and democrats are typically pro-choice. I do acknowledge that there are pro-choice republicans and pro-life democrats which is why I am interested to see the correlation. I will be looking at the 2020 presidential election data per state to show whether the result for that year was red or blue. I will compare that to the number of abortions per state in the year 2020.

This geospatial map shows the number of abortions per 1,000 women ages 15-44 per state in the year 2020. It is color coded by light blue to dark blue. The darker the color blue, the more abortions recorded for that state. For example, Missouri is a light shade of blue, showing a low number of abortions, and New York is a dark shade of blue showing a high number of abortions.

This geospatial map shows whether states voted for Trump or Biden in the 2020 presidential election. It is color coded by red and blue. Trump states are red and Biden states are blue.

This bar graph is showing the number of abortions per 1,000 women ages 15-44 per state in the year 2020. The order of the states is from most abortions to least abortions. This graph is also color coded. Each bar is either red or blue to show whether the state voted for Trump or Biden in the year 2020. Red is for Trump and blue is for Biden. This graph shows a correlation between number of abortions and whether that state voted republican or democratic in 2020. Overall, the graph goes from blue (showing a relatively higher number of abortions) to red (showing a relatively lower number of abortions). There are a few states that do not fit these criteria. Florida, North Carolina, Kansas, and Oklahoma are all Trump voting states with a higher number of abortions. Arizona, New Hampshire, and Wisconsin are all Biden voting states with a lower number of abortions.

This graph shows the correlation between number of abortions per 1,000 women ages 15-44 per state and the proportion of Biden voters in that state. The correlation line for Biden voting states is showing that relatively, the states with more abortions had a higher percentage of Biden votes in 2020. The correlation line for Trump voting states is showing that relatively, the states with more abortions had a higher percentage of Biden votes in 2020. One point to note is that Florida and North Carolina have both the highest number of abortions and Biden votes for states that Trump won. Similarly, Wisconsin and Arizona have two of the lowest abortion rates and have the lowest number of Biden votes for states that Biden won in.

In conclusion, my hypothesis was correct. Overall, there is a correlation between number of abortions per state in 2020, and if that state voted for Trump or Biden in the 2020 Presidential Election. There are a few states that are outliers in this statement as mentioned above, but I found that republican states with higher abortion rates did have a high percentage of Biden voters, and democratic states with lower abortion rates had a lower percentage of Biden voters. I believe that this is important data to be aware of now that the matter of abortion is up to the states. If republican states like Florida and North Carolina no longer allow abortions, women will be heavily affected because both states had a very high abortion rate in relation to all other states. When this data becomes available, an interesting thing to look at would be abortion rates in 2022 per state and if a republican or democratic governor won the state election. There is a lot to observe here with this data and may help make predictions for the future.