Article Text
Abstract
Background The purpose of this study was to examine the association between racial and economic segregation and diabetes mortality among US counties from 2016 to 2020.
Methods We conducted a cross-sectional ecological study that combined county-level diabetes mortality data from the National Vital Statistics System and sociodemographic information drawn from the 2016–2020 American Community Survey (n=2380 counties in the USA). Racialized economic segregation was measured using the Index Concentration at the Extremes (ICE) for income (ICEincome), race (ICErace) and combined income and race (ICEcombined). ICE measures were categorised into quintiles, Q1 representing the highest concentration and Q5 the lowest concentration of low-income, non-Hispanic (NH) black and low-income NH black households, respectively. Diabetes was ascertained as the underlying cause of death. County-level covariates included the percentage of people aged ≥65 years, metropolitan designation and population size. Multilevel Poisson regression was used to estimate the adjusted mean mortality rate and adjusted risk ratios (aRR) comparing Q1 and Q5.
Results Adjusted mean diabetes mortality rate was consistently greater in counties with higher concentrations of low-income (ICEincome) and low-income NH black households (ICEcombined). Compared with counties with the lowest concentration (Q1), counties with the highest concentration (Q5) of low-income (aRR 1.96; 95% CI 1.81 to 2.11 for ICEincome), NH black (aRR 1.32; 95% CI 1.18 to 1.47 for ICErace) and low-income NH black households (aRR 1.70; 95% CI 1.56 to 1.84 for ICEcombined) had greater diabetes mortality.
Conclusion Racial and economic segregation is associated with diabetes mortality across US counties.
- DIABETES MELLITUS
- Health inequalities
- SOCIAL CLASS
- ETHNIC GROUPS
- POVERTY
Data availability statement
Data are available in a public, open access repository. Data are publicly available from the US Census Bureau (https://data.census.gov/) and CDC WONDER (https://wonder.cdc.gov/) websites.