Housing instability is linked to numerous health outcomes, but the specific impact of eviction from renter-occupied households, an event that has immediate implications for residential stability for low-income individuals, on sexually transmitted infections (STI) rates has not been adequately studied.
We examined county-level associations between eviction rates in 2014 and rates of chlamydia and gonorrhea in the following year using publicly available data sources (Eviction Lab National Database and AtlasPlus, respectively). Descriptive statistics compared medians and nonparametric distributions with Krusal-Wallis tests. Linear regression was used to compare tertile categories of eviction rates and STI rates while controlling for potential confounders.
Median rates of chlamydia in counties with low, medium, and high rates of eviction were 229, 270, and 358 cases per 100,000 population, respectively (P < 0.001). The corresponding median rates of gonorrhea were 25, 37, and 75 cases per 100,000 population (P < 0.001). These associations remained statistically significant after controlling for all covariates in adjusted models. The beta coefficients and 95% confidence intervals (95% CI) for chlamydia and gonorrhea comparing high to low county-level eviction rates were 63.8 (95% CI, 45.1–82.5) and 20.4 (95% CI, 13.5–27.4), respectively. Similar associations were observed across levels of poverty and in both metropolitan and nonmetropolitan counties.
County-level eviction rates are associated with chlamydia and gonorrhea rates in a significant and robust way independent of other known predictors of STI. These results suggest that evictions result in residential instability in a way that may increase STI risk.
County-level eviction rates in the United States are associated with chlamydia and gonorrhea rates in a significant and robust way independent of other known predictors of sexually transmitted infection.
From the *Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT;
†Department of Sociology, American University, Washington, DC; and
‡Department of Social and Behavioral Sciences, Yale School of Public Health, New Haven, CT
Conflicts of Interest: None declared.
Sources of Funding: This work was supported in part by National Institutes of Health grant 1R01MH110192.
Correspondence: Linda Niccolai, PhD, Yale School of Public Health, 60 College St, New Haven, CT 06520. E-mail: firstname.lastname@example.org.
Received for publication May 15, 2018, and accepted August 18, 2018.
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