This selection of the scatterplot shows the correlation between Median Household Income (MHI) and Percent Obesity. As we can see there is a strong correlation between these two metrics. As the MHI increases the percentage of people who are obese steadily decreases. Further analysis might be warranted of the states and regions to see if there is an area in America where this trend is stronger.
This selection of the scatterplot shows the correlation between MHI and the percentage of people who smoke across America. Like the previous correlation (MHI vs Obesity) we can see a strong correlation between the two metrics. As MHI increases, the percentage of people who smoke steaditly decreases. Maryland has the highest MHI and one of the lowest percentage of smokers. Again, further analysis might be warranted to see if there is an area in America where this trend is stronger.
This selection of the scatterplot shows the correlation between the percentage of People in Poverty (PIP) and the amount of people without healthcare. As This chart shows, there is a strong correlation between the two metrics; as the PIP increases so does the amount of people without healthcare. This adds to the overall trend in the dataset that as the amount of income increases, the amount of health related issues decreases. At this point I would say further analysis is recommended of the states and regions to see if there is some significance to the trends in certain parts of America.