EXHIBIT 4.
Change in US county-level kidney failure incidence per million, by poverty quintile, 2000–17
| Kidney failure incidence (per million US adults) |
||||
|---|---|---|---|---|
| Period 1 (2000–05) | Period 2 (2006–11) | Period 3 (2012–17) | Adjusted change from period 1 to period 3 | |
| National estimates | 471.7 | 474.3 | 458.5 | −13.2*** |
| Model 1 (unadjusted) | ||||
| Highest poverty quintile | 641.0 | 662.8 | 691.2 | 50.3*** |
| Lowest poverty quintile | 356.0 | 378.1 | 377.1 | 21.2*** |
| Differencea | 285.0 | 284.7 | 314.1 | 29.1*** |
| Model 2 | ||||
| Highest poverty quintile | 664.0 | 678.2 | 692.5 | 28.5** |
| Lowest poverty quintile | 375.0 | 378.2 | 354.2 | −20.8*** |
| Differencea | 289.0 | 300.0 | 338.3 | 49.3*** |
| Model 3 | ||||
| Highest poverty quintile | 540.6 | 561.2 | 570.9 | 30.4** |
| Lowest poverty quintile | 435.5 | 427.4 | 398.2 | −37.3**** |
| Differencea | 105.1 | 133.8 | 172.7 | 67.7**** |
| Model 4 | ||||
| Highest poverty quintile | 522.2 | 551.4 | 556.4 | 34.2** |
| Lowest poverty quintile | 430.5 | 429.6 | 416.8 | −13.7** |
| Differencea | 91.7 | 121.8 | 139.6 | 47.9**** |
| Model 5 | ||||
| Highest poverty quintile | 489.9 | 502.5 | 536.3 | 37.4*** |
| Lowest poverty quintile | 450.7 | 433.0 | 430.5 | −20.3**** |
| Differencea | 48.2 | 69.5 | 105.8 | 57.7**** |
| Model 6 | ||||
| Highest poverty quintile | 494.0 | 501.9 | 532.6 | 38.6*** |
| Lowest poverty quintile | 451.2 | 435.2 | 432.5 | −18.7*** |
| Differencea | 42.8 | 66.6 | 100.1 | 57.3**** |
SOURCE Authors’analyses of Medical Evidence Report data (form CMS 2728) and Census Bureau annual county population estimates, 2000–17. NOTES National estimates are age and sex adjusted. Model 2 includes the indicators for poverty quintile, period, and their interaction (poverty quintile × period), as well as age, sex, and a linear time trend. Model 3 adds county-level proportions of the population that were Black, Hispanic or Latino, American Indian or Native American, or Asian or Pacific Islander. Model 4 adds county-level sociodemographic characteristics (urban or rural designation, uninsurance rate, unemployment rate, and educational attainment). Model 5 adds county-level prevalence of diagnosed diabetes among all adults. Model 6 adds county-level number of dialysis facilities per capita and number of active nonfederal physicians per 1,000 population. All models are weighted by the county’s adult population. Standard errors are clustered at the county level. Poverty quintiles are defined in the text.
Difference between highest and lowest poverty quintiles.
p < 0.05
p < 0.01
p < 0.001