Justice and Public Policy

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 Introduction: Universal healthcare in the United States is a highly debated topic. Having access to health insurance provides several benefits, including mental and physical health services. Those without access to health insurance are often left without mental health treatment and/or diagnosis. This is concerning due to data that suggests that persons with a history of mental illness who later lost health insurance services are at a greater risk of committing crime (Jácome, 2021), and mental health history increases the likelihood of incarceration (Meier, 2021). Previous studies also suggest that increased access to health insurance for all persons decreased incentives to commit crime (Aslim, 2019) and that expanded Medicaid decreased violent crime rates (Doleac, 2018). Because of this information, this study seeks to examine the relationship between persons without health insurance and violent crime rates in using the 2012 states data information. Results may suggest policy recommendations for reducing medical co-pays for incarcerated persons (Initiative, 2017) and increasing health insurance accessibility for the general public. 

Data and Methods: In order to test our research question, we derived violent crime rates and persons without health insurance percentages from the 2012 States data (Bachmann & Schutt, 2020). The data was imported into SPSS, Excel and Datawrapper. Included in this study is the assault rate per 100k, the murder rate per 100k, and the percent of persons without health insurance in all 50 states. Assault is a violent attack from one person to another and murder is a violent attack that led to the death of another person (Offense definitions, n.d.). The outcome of interest is to find a statistically significant relationship between persons without health insurance and physical violent crime rates in order to support policy that seeks to limit medical co-pay costs for incarcerated citizens and support universal health care policy. 

In order to conclude a relationship between persons without health insurance and violent crime rates, a Pearson correlation matrix was computed to analyze the Pearson Correlation and the significance value. 

Results: The bivariate Pearson correlation matrix between percent of persons without health insurance and murder rate per 100k was 0.527. Therefore, the data shows a moderate correlation between the two variables. Moreover, the Pearson correlation between percent of persons without health insurance and assault rate per 100k was 0.479, therefore, the data shows a moderate correlation between the two variables. The two scatterplot graphs of persons without health insurance and assault rater per 100k and murder rate per 100k display the moderate correlations. The p-value for the assault rate per 100k and murder rate per 100k were both 0.001, which is less than the significance value (0.01), concluding a statistical significance that surpasses the odds of chance (0.001 < 0.01). These results support prior research and studies that there is a relationship between persons without health insurance coverage and violent crime rates.  The data is represented in both scatterplots and choropleth maps. The scatter plots help visually represent the correlation between physical assault and uninsurance rates. The two choropleth maps are used as a spatial representation of where in the United States assault rates and uninsurance rates are high, respectively. Lighter colors represent low data points and gradually get darker to represent high data points. In comparing the two choropleth maps, we can again see a moderate correlation between high uninsurance percentages and high assault rates. States with lower percentages of persons who are uninsured are more likely to have lower assault rates. For example, 10.4% of persons in Maine are uninsured, and they have the lowest assault rate at 59.2 cases per 100k. On the other side, Texas has the highest percentage of persons who are uninsured at 26.1% and has an assault rate of 299 cases per 100k.

Conclusion: Our research support previous literature that suggests health coverage has an effect on criminal behavior. Our findings are relevant to the debates surrounding Universal Health Care and support policy initiatives to reduce medical co-pays for incarcerated persons (Initiative, 2017).  This data can be used as evidence in favor for free healthcare in the United States. This data can also be used to analyze which states struggle the most with uninsurance percentages. The study should be reanalyzed with more recent data from 2021 to determine a more current correlation. The study should be conducted each year to track any trends and changes to assault rates and uninsurance percentages.

References:  

Aslim, Mungan, M. C., Navarro, C. I., & Yu, H. (2022). The Effect of Public Health Insurance on Criminal Recidivism. Journal of Policy Analysis and Management, 41(1), 45–91. https://doi.org/10.1002/pam.22345   Bachman, R. D., & Schutt, R. K. (2020). Fundamentals of research in criminology and criminal justice (5th ed.). SAGE Publications, Inc.  Initiative, P. P. (2017, April 19). The steep cost of medical co-pays in prison puts health at risk. Prison Policy Initiative. https://www.prisonpolicy.org/blog/2017/04/19/copays/ Jácome, E. (2021, July). How better access to mental health care can reduce crime. Retrieved April 5, 2022, from https://siepr.stanford.edu/publications/policy-brief/how-better-access-mental-health-care-can-reduce-crime Jennifer L Doleac. (2018). New evidence that access to health care reduces crime. In Up Front [BLOG]. The Brookings Institution. Meier, M. (2021). RESEARCH WEEKLY: Serious mental illness and likelihood of incarceration after arrest. Treatment Advocacy Center. https://www.treatmentadvocacycenter.org/fixing-the-system/features-and-news/4204-research-weekly-serious-mental-illness-and-likelihood-of-incarceration-after-arrest- Offense definitions. (n.d.). FBI. https://ucr.fbi.gov/crime-in-the-u.s/2017/crime-in-the-u.s.-2017/topic-pages/offense-definitions