Population-level predictors of sexually transmitted infection rate changes in Missouri: an ecological study

Abstract

Background: Sexually transmitted infection rates continue to increase across the US, further developing health disparities and economic burdens of disease, especially as migration occurs. In this study, we aim to assess the relationship between STI rates and population-level variables from 2008 to 2017 at the county level in Missouri.

Methods: Two data sources were used: STI rates of chlamydia, gonorrhea, syphilis, HIV reported to Missouri DHSS and ACS 1-year county population estimates. Linear regression models and ANOVA tests were conducted in SPSS for each STI from year-to-year and 2008-2017. Covariates included in the analyzes were county-level income, employment rate, race, ethnicity, age, and percent poverty. Further, Akaike Information Criterion tests were performed to indicate the best predictor models and averaged standardized beta values.

Results: Significant relationships among STI rates and population growth were identified. Chlamydia, syphilis, and HIV were positively associated with population growth from 2008 to 2017 (β = 0.15; β = 0.01; β = 0.05, respectively). Gonorrhea was negatively associated with population growth (β = - 0.02) but positively associated with unemployment rates (β = 0.01) highlighting the need to address population growth, as well as other variables in a population.

Conclusions: There seems to be a positive relationship among population change and rates of STIs. As populations change, rates of STIs change. Moving forward, quantitative work should be conducted in various states and the nation to understand this relationship in different contexts. Future studies should be qualitative word focused on county health departments and community health improvement plans. Lastly, public policy should be implemented to buffer the impact of migration on health outcomes.

Keywords: HIV; Population health; Sexually transmitted infections.