When Risk Meets Place: Neighborhood Conditions Amplify the Link between Binge Drinking and Mental Health In a GIS-Based Analysis of Florida

Background and Purpose
Mental health conditions, including depression and frequent mental distress, remain highly prevalent in the United States and vary substantially across neighborhoods. Binge drinking is a well established behavioral risk factor associated with poor mental health outcomes, while neighborhood socioeconomic conditions shape exposure to stressors and access to resources. Although prior research has examined these factors independently, fewer studies have investigated how behavioral risk and structural vulnerability interact across place. This study applies a spatial analytic framework to examine whether neighborhood socioeconomic vulnerability moderates the association between binge drinking prevalence and population level depression and frequent mental distress across census tracts in Florida.

Methods
We conducted a neighborhood level spatial analytic study using 2020 census tract data from Florida derived from the CDC PLACES dataset and the Social Vulnerability Index. The analytic sample included census tracts with complete data across all study variables . Outcomes included tract level prevalence of diagnosed depression and frequent mental distress. Primary predictors were binge drinking prevalence (mean = 14.55, SD = 2.76) and socioeconomic vulnerability (mean = 59.81, SD = 26.64). Covariates included physical inactivity (mean = 27.57, SD = 7.09), obesity (mean = 30.80, SD = 5.60), and short sleep duration (mean = 34.35, SD = 4.63). Multivariable linear regression models were estimated with interaction terms to assess effect modification. Geographic Information Systems techniques were used to generate choropleth maps and spatial overlays to identify clustering and co occurrence patterns. Model based predicted values were visualized using contour plots to examine joint effects across levels of risk.

Results
Higher neighborhood binge drinking prevalence and higher socioeconomic vulnerability were each associated with higher levels of depression (mean = 18.24, SD = 2.42) and frequent mental distress (mean = 15.27, SD = 2.74). Interaction effects were statistically significant for both depression (B = 0.003, 95 percent CI = 0.002 to 0.004) and mental distress (B = 0.003, 95 percent CI = 0.002 to 0.003), indicating that the association between binge drinking and mental health outcomes was stronger in more socioeconomically vulnerable neighborhoods. The joint presence of high binge drinking and high vulnerability corresponded to the highest predicted levels of mental health burden. Geographic Information Systems visualizations revealed non random spatial patterning, with co occurrence of behavioral risk and structural disadvantage aligning with areas of concentrated mental health burden across Florida. Model fit was substantial, particularly for mental distress (R squared = 0.864) and depression (R squared = 0.549).

Conclusion and Implications
Neighborhood socioeconomic vulnerability amplifies the association between binge drinking and mental health burden, supporting a contextual amplification perspective. By integrating Geographic Information Systems, interaction modeling, and neighborhood level data, this study advances a more precise understanding of place based mental health disparities. Implications for social work practice and policy include the need for geographically targeted, data informed interventions that address both substance use and structural inequities. Spatially informed strategies may improve the precision and effectiveness of interventions to reduce mental health disparities and promote population well being.