Sleep disorder and residential segregation in Cleveland, Ohio: analysis of the index of concentration at the extremes (ICE)

Residential segregation is a fundamental structural determinant of health that generates social and spatial inequalities, yet its relationship with clinically diagnosed sleep disorders remains poorly understood. This study examined the association between neighborhood residential segregation and clinically diagnosed sleep disorders among 165,669 individuals residing in 265 census tracts in Cleveland, Ohio. Residential segregation was measured using the Index of Concentration at the Extremes (ICE), which captures racial segregation (ICE-Race), income segregation (ICE-Income), and racialized economic segregation (ICE-Race-Income). Logistic regression was used to estimate the odds of a sleep disorder diagnosis across quintiles of neighborhood advantage, comparing the most advantaged neighborhoods (Q5: predominantly White/highest income) with the most disadvantaged neighborhoods (Q1: predominantly Black/lowest income). In unadjusted models, residents of the most advantaged neighborhoods had significantly lower odds of a sleep disorder diagnosis than residents of the most disadvantaged neighborhoods. Specifically, individuals living in predominantly White neighborhoods had 25% lower odds of diagnosis (OR = 0.75, p < .001), those living in the highest-income neighborhoods also had 25% lower odds (OR = 0.75, p < .001), and those living in predominantly White, high-income neighborhoods had 24% lower odds (OR = 0.76, p < .001). After simultaneously adjusting for all ICE measures and individual demographic and health characteristics, only income segregation remained statistically significant, but the association reversed direction. Individuals living in the highest-income neighborhoods had 11% higher odds of a sleep disorder diagnosis than those in the lowest-income neighborhoods (OR = 1.11, p < .01). These findings suggest that the relationship between residential segregation and clinically diagnosed sleep disorders is complex and influenced by both neighborhood context and individual characteristics. The reversed association for income segregation may reflect greater healthcare access, higher screening and diagnostic rates, private insurance coverage, and potentially higher levels of social isolation in affluent neighborhoods.