Mental Health Mystery
What factors might be causing poor mental health in the U.S., and what can we do to address them?
The past few decades have seen a dramatic rise in the degree to which mental health issues are recognized and discussed. In the age of social media, topics like anxiety and depression are frequently talked about online, and the stigmas around struggles like these are diminishing. Arguably, awareness of mental health issues is at an all-time high. Yet, since this widespread awareness is so new, a lot is still unknown about what factors increase the risk of mental health struggles, and what methods are effective for treating them. Traditionally, methods like talk therapy and prescription of psychiatric medications have been the go-to treatments, but recently, interest in behavioral treatments like meditation and exercise has gained traction, as research points to their effectiveness in relieving the negative symptoms of common mental health disorders.
Using data from the University of Wisconsin Population Health Institute’s County Health Rankings & Roadmaps program, I examined what indicators are positively and negatively correlated with three indicators of poor mental health: Poor mental health days, Frequent mental distress, and Suicides. This data is collected annually across the United States on a county-wide level, and the dataset I used comes from 2021. Before discussing factors that I did find to be strongly correlated, I’d like to address the relationship that surprised me the most: across the nearly 3200 counties in the United States, the number of mental health providers, relative to the total population of the county, seems to be almost not at all correlated with the poor mental health indicators I examined. The Pearson correlation coefficients between mental health providers and poor mental health days, frequent mental distress, and suicides were -0.063, -0.128, and 0.0085, respectively. This lack of correlation could indicate many things: perhaps counties just have a number of mental health care providers relative to their total population, regardless of the number of people with mental health struggles, or maybe mental health professionals are underutilized due to access barriers to this type of care. But it is also possible that traditional mental health care as provided by these professionals is not the most effective way to treat these illnesses and improve mental health outcomes in a community. What factors, then, are strongly correlated with poor mental health, and how can this data be leveraged to improve mental health treatment strategies and prevention measures?
For most indicators, the correlation to suicides varies greatly from that of poor mental health days and frequent mental distress, so from here on I’ll only be discussing the latter two, attempting to weed out what influences day-to-day mental health rather than examining the much more extreme and rare case of suicides. Most of the moderate to strongly correlated indicators can be broken into two important categories: structural indicators and behavioral indicators. Structural indicators are things I define as indicative of a person/county’s socioeconomic status: these are things that were they improved, could likely improve mental health, but which individuals can’t necessarily take actions to change. The variables of food insecurity, children in poverty, unemployment, air pollution, and disconnected youth each had positive correlations with poor mental health days and frequent mental distress. The correlation values of these variables ranged from 0.39/0.48 for the disconnected youth indicator, to 0.72/0.77 for food insecurity (values formatted as correlation to poor mental health days/correlation to frequent mental distress). It’s highly logical that not having access to necessities like food, clean air, and social networks would negatively impact mental health, but no one can prescribe fixing these things as a mental health treatment. Larger structural changes have to be made to improve the overall well-being of communities, and improved mental and physical health will follow.
However, the behavioral variables indicate that there are actual changes people can make to their routines to improve their mental health. Five behavioral indicators of interest are insufficient sleep, adult smoking, physical inactivity, driving alone to work, and excessive drinking. A chart of each behavioral indicator and its correlation to negative mental health outcomes is shown below.
The county-level data points for each behavioral variable vs. poor mental health days have also been graphed to help visualize the strength of each relationship.
The data show a moderate to strong positive correlation between insufficient sleep, adult smoking, physical inactivity, and poor mental health. There is a weak positive correlation between driving alone to work and poor mental health, and strangely, a moderately strong negative correlation between excessive drinking and poor mental health. Seeing mental health care professionals is certainly an important treatment step for many, but the data suggest individuals should also focus on getting enough sleep, being active, not smoking, finding carpool buddies, and…drinking excessively (please don’t do this) to improve their mental health.
Of course, without further research, it is impossible to say whether, for instance, people have improved mental health when sleeping enough or whether having poor mental health in the first place inhibits their ability to get sufficient sleep. This is to say that the direction of potential causation between these variables cannot be concluded from this data, but nevertheless, it can help inform what factors are related to mental health and just may be the solution to improving it. As mental health becomes increasingly recognized, we should focus additional research on alternative behavioral treatments, as well as continue investigating the structural factors that lead communities to have poor mental health.
