Kindness is all it takes sometimes
The correlation between mental health and households in poverty
When looking at the data and general correlations between variables such as income, health, and race among others, the potential to find an unusual relationship was so large it was practically overwhelming. However, after combining my data and looking at all of the relationships I couldn’t help but notice the mental health percentages in counties. I thought this was interesting because I’ve always been interested in mental health, and wanted to find a correlation relating back to this. It wasn’t hard to think of one though as countless conversations with my peers went through my head, little comments that were dropped during the conversation. Thus the question to prove and discuss is what is the relationship between low-income families and mental health? Is there one, and how do they correlate?
From a theoretical stance, at first income and mental health may not make sense regarding sharing a relationship. However, when thinking realistically it does make sense that there could be some correlation, as stress regarding money does have a dire impact on mental health. This is also important to note that those with lower income might not be able to afford the help they need, leading to worsening mental health. However, this relationship can only truly be proven by running statistical tests to see the percentage of correlation and how one variable impacts the other.
Looking at the data and the numbers, the first step that was done to analyze this relationship was to combine all 3 data sources into one larger data table where the numbers were pulled from there. The data sources themselves contained information pertaining to health statistics in both physical and mental, employment percentages, and county-wide data in a more generalized sense. A number of tests regarding correlation were run to first get a sense of all of the potential correlations to ensure the tests that were being done weren’t ones for variables that already had a strong correlation. Next was the selection of variables. The first variable was the “Number of poor mental health days (in a week) raw value” which depicted how many days in a week a person was struggling with their mental health. The next variable selected was “pct_family_poverty”. This essentially depicts the percentage of families that are in poverty in a county. Another variable selected was “Median_Household_income_2019”, which is relatively self-explanatory but provided statistics for the median household income in 2019 per county. With these selected variables, a number of linear regression tests were run to get a better insight into correlation statistics. Regarding the percentage of family poverty and mental health raw data, it was shown that a one percent increase of families in poverty in a county increased the number of days people struggled with mental health in that county by 0.19 percentage points.
When comparing the percentages of families in poverty with suicide rates, there was a shocking 0.57 percentage point regarding the percentage of families increasing by every 1 percent.
A number of visuals were then created, predominately scatterplots, to visualize this relationship and change in statistics. As the following visuals show, the more of an increase there is regarding income in both raw data and in 2019, the lower both suicide rates raw data and the number of poor mental health days went. Running a general test regarding income and then percentages of families that are in poverty provide proper insight and visualization of the fact that lower-income families are more likely to struggle with mental health in both these more specified charts and general income charts.
Thinking about this from a critical lens, a fair assumption can be made that it may be due to the fact that those in lower-income homes are not able to afford the mental health care and support that they need. However, this is still a completely overlooked issue in general as insurance and therapy can be expensive, especially if one needs to take medication for any disorders related to mental health. The visualizations certainly speak for themself, that there is clearly a connection between households in poverty and those suffering from bad mental health. However, it’s what we do with this data and revelation that can make a difference and help others. This is a sign that we need to be providing more accessible resources for those struggling, and that both the economy and our nation are in deep trouble if people are so stressed from finances that they are potentially driven to do something drastic. Take care of the ones you love, check in on friends and family in general and strive to be kind to strangers. You never know who is having a bad day, and sometimes all it takes is an act of kindness to potentially save a life.
