Population Income and Longitudinal Trends in Living Kidney Donation in the United States
Bibliographic record
Abstract
Living kidney donation is declining in the United States. We examined longitudinal trends in living donation as a function of median household income and donor relation to assess the effect of financial barriers on donation in a changing economic environment. The zip code-level median household income of all 71,882 living donors was determined by linkage to the 2000 US Census. Longitudinal changes in the rate of donation were determined in income quintiles between 1999 and 2004, when donations were increasing, and between 2005 and 2010, when donations were declining. Rates were adjusted for population differences in age, sex, race, and ESRD rate using multilevel linear regression models. Between 1999 and 2004, the rate of growth in living donation per million population was directly related to income, increasing progressively from the lowest to highest income quintile, with annualized changes of 0.55 (95% confidence interval [95% CI], 0.14 to 1.05) for Q1 and 1.77 (95% CI, 0.66 to 2.77) for Q5 (P<0.05). Between 2005 and 2010, donation declined in Q1, Q2, and Q3; was stable in Q4; and continued to grow in Q5. Longitudinal changes varied by donor relationship, and the association of income with longitudinal changes also varied by donor relationship. In conclusion, changes in living donation in the past decade varied by median household income, resulting in increased disparities in donation between low- and high-income populations. These findings may inform public policies to support living donation during periods of economic volatility.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".