Zhang Ye, Gerdtham Ulf-G, Rydell Helena, Jarl Johan
Health Economics Unit, Department of Clinical Sciences, Lund University, Lund, Sweden.
Department of Economics, Lund University, Lund, Sweden.
Transplant Direct. 2018 Feb 2;4(2):e346. doi: 10.1097/TXD.0000000000000764. eCollection 2018 Feb.
Few studies have examined the association between individual-level socioeconomic status and access to kidney transplantation. This study aims to investigate the association between predialysis income and education, and access to (i) the kidney waitlist (first listing), and (ii) kidney transplantation conditional on waitlist placement. Adjustment will be made for a number of medical and nonmedical factors.
The Swedish Renal Register was linked to national registers for adult patients in Sweden who started dialysis during 1995 to 2013. We employed Cox proportional hazards models.
Nineteen per cent of patients were placed on the waitlist. Once on the waitlist, 80% received kidney transplantation. After adjusting for covariates, patients in the highest income quintile were found to have higher access to both the waitlist (hazard ratio [HR], 1.73; 95% confidence interval [CI], 1.53-1.96) and kidney transplantation (HR, 1.33; 95% CI, 1.16-1.53) compared with patients in the lowest income quintile. Patients with higher education also had better access to the waitlist and kidney transplantation (HR, 2.16; 95% CI, 1.94-2.40; and HR, 1.16; 95% CI, 1.03-1.30, respectively) compared with patients with mandatory education.
Socioeconomic status-related inequalities exist with regard to both access to the waitlist, and kidney transplantation conditional on listing. However, the former inequality is substantially larger and is therefore expected to contribute more to societal inequalities. Further studies are needed to explore the potential mechanisms and strategies to reduce these inequalities.
很少有研究探讨个体层面的社会经济地位与肾移植可及性之间的关联。本研究旨在调查透析前收入和教育程度与（i）肾脏等候名单（首次列入）以及（ii）等候名单登记后的肾移植可及性之间的关联。将对一些医学和非医学因素进行调整。
瑞典肾脏登记处与瑞典1995年至2013年期间开始透析的成年患者的国家登记处相链接。我们采用了Cox比例风险模型。
19%的患者被列入等候名单。一旦列入等候名单，80%的患者接受了肾移植。在对协变量进行调整后，发现收入最高五分位数的患者与收入最低五分位数的患者相比，进入等候名单（风险比[HR]，1.73；95%置信区间[CI]，1.53 - 1.96）和接受肾移植（HR，1.33；95% CI，1.16 - 1.53）的机会更高。与接受义务教育的患者相比，受教育程度较高的患者进入等候名单和接受肾移植的机会也更好（分别为HR，2.16；95% CI，1.94 - 2.40；以及HR，1.16；95% CI，1.
