Significant Predictors of Suicide Rates in the United States: A Multiple Regression Analysis - Alexa L Darak; Gary Popoli (Undergraduate Research Journal for the Human Sciences, 2024)
Inspired by Stack's (2021) research, this study investigated the influence of 19 variables on suicide rates across all 50 United States. The variables included political party, gun ownership, registered guns, religion, alcohol consumption, state safety, depression, marriage, divorce, domestic violence, race, mean elevation, and region. Regression analyses revealed that gun ownership significantly impacts suicide rates, with stricter firearm laws correlating with lower suicide rates. Other crucial contributors to suicide risk were alcohol consumption, domestic violence, marital status, divorce, mean elevation, and political party affiliation. The five most statistically significant predictor variables were gun ownership, divorce rates, percentage of White individuals, percentage of Black individuals, and mean elevation. While gun ownership, divorce rate, and mean elevation increased suicide rates, the percentage of Black and White individuals living in a state helped reduce suicide rates. The results emphasize the importance of considering multiple variables when formulating preventative strategies and policies to address this complex issue. By understanding the intricate interplay of these factors, policymakers and mental health professionals can develop targeted interventions to reduce suicide rates effectively.
Keywords: suicide; predictors; correlation; rate; multiple regression