3 - (SYM 13) Using Geospatial Data Analysis to Examine Impacts of Neighborhood Disadvantage on Anxiety Symptoms During COVID-19

Abstract Body
Etiological research on anxiety disorders has focused primarily on individual-level risk factors. There is a need to understand socio-contextual factors that impact anxiety, particularly in the context of socio-contextual stressors, to inform prevention and intervention efforts at multiple ecological levels. Neighborhood disadvantage is one socio-contextual factor that predicts a range of health outcomes but is rarely examined in a mental health context. We used geospatial data analysis to examine associations between neighborhood disadvantage and anxiety symptoms during COVID-19, a unique socio-contextual stressor. 
Participants were 923 adults in Florida recruited via Qualtrics (M = 42 yrs; 69% female; 67% White; 68% Non-Hispanic) asked to complete 3 waves of data collection in April 2020, May 2020, and January 2021. Participants’ addresses were geocoded using 2020 census data to derive the Area Deprivation Index, an index of neighborhood disadvantage (M = 4.9, range 1-10 in this sample; Kind & Buckingham, 2018). Individual-level factors (gender, race, SES, and level of COVID knowledge) were collected at baseline. General anxiety and COVID-specific worry were assessed at all 3 timepoints. Multilevel modeling was used to examine associations between neighborhood disadvantage and general anxiety and COVID-specific worry over time, controlling for individual-level factors.
General anxiety (B = -0.19, p = .008) and COVID-specific worry (B = -1.04, p < .001) decreased significantly over time. Contrary to our hypothesis, greater neighborhood disadvantage was associated with lower general anxiety (B = -0.05, p = .034) and COVID-specific worry (B = -0.16, p = .011), controlling for theoretically relevant individual factors (i.e., gender, race, SES, and COVID knowledge). Neighborhood disadvantage was not associated with rate of change in general anxiety over time but was associated with rate of change in COVID-specific worry, such that individuals living in more disadvantaged neighborhoods exhibited less decrease in COVID-specific worry over time (B = 0.12, p = .026).
Geospatial data analysis provides novel insight into anxiety risk and resilience. Individuals living in disadvantaged neighborhoods may self-report less anxiety on average but may experience more prolonged effects of socio-contextual stressors on anxiety. Future research should examine whether specific aspects of neighborhood disadvantage (e.g., housing quality, access to resources) confer greatest risk for anxiety maintenance in the context of stressors.