BACKGROUND: Incidence rates of renal replacement therapy (RRT) for end-stage renal disease vary considerably worldwide. This study examines the independent association between the general population, health care system and renal service characteristics and RRT incidence rates. METHODS: RRT incidence data (2003-2005) were obtained from renal registries; general population age and health and macroeconomic indices were collected from secondary sources. Renal service organization and resource data were obtained through interviews and questionnaires. Linear regression models were built to establish the factors independently associated with RRT incidence, stratified by the Human Development Index where required. False discovery rate (FDR) correction was adjusted for multiple testing. RESULTS: Across the 46 countries (population 1.25 billion), RRT incidence rates ranged from 12 to 455 (median 130) per million population. Gross domestic product (GDP) per capita [incidence rate ratio (IRR): 1.02 per $1000 increase, P(FDR) = 0.047], percentage of GDP spent on health care (IRR: 1.11 per % increase, P(FDR) = 0.006) and dialysis facility reimbursement rate relative to GDP (IRR: 0.76 per GDP per capita-sized increase in reimbursement rate, P(FDR) = 0.007) were independently associated with RRT incidence. In more developed countries, the private for-profit share of haemodialysis facilities was also associated with higher incidence (IRR: 1.009 per % increase, P(FDR) = 0.003). CONCLUSIONS: Macroeconomic and renal service factors are more often associated with RRT incidence rates than measured demographic or general population health status factors.
BACKGROUND: Incidence rates of renal replacement therapy (RRT) for end-stage renal disease vary considerably worldwide. This study examines the independent association between the general population, health care system and renal service characteristics and RRT incidence rates. METHODS: RRT incidence data (2003-2005) were obtained from renal registries; general population age and health and macroeconomic indices were collected from secondary sources. Renal service organization and resource data were obtained through interviews and questionnaires. Linear regression models were built to establish the factors independently associated with RRT incidence, stratified by the Human Development Index where required. False discovery rate (FDR) correction was adjusted for multiple testing. RESULTS: Across the 46 countries (population 1.25 billion), RRT incidence rates ranged from 12 to 455 (median 130) per million population. Gross domestic product (GDP) per capita [incidence rate ratio (IRR): 1.02 per $1000 increase, P(FDR) = 0.047], percentage of GDP spent on health care (IRR: 1.11 per % increase, P(FDR) = 0.006) and dialysis facility reimbursement rate relative to GDP (IRR: 0.76 per GDP per capita-sized increase in reimbursement rate, P(FDR) = 0.007) were independently associated with RRT incidence. In more developed countries, the private for-profit share of haemodialysis facilities was also associated with higher incidence (IRR: 1.009 per % increase, P(FDR) = 0.003). CONCLUSIONS: Macroeconomic and renal service factors are more often associated with RRT incidence rates than measured demographic or general population health status factors.
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Authors: Wim van Biesen; Moniek W M van de Luijtgaarden; Edwina A Brown; Jean-Pierre Michel; Barbara C van Munster; Kitty J Jager; Sabine N van der Veer Journal: Nephrol Dial Transplant Date: 2015-08-12 Impact factor: 5.992
Authors: Roberto Pecoits-Filho; Ikechi G Okpechi; Jo-Ann Donner; David C H Harris; Harith M Aljubori; Aminu K Bello; Ezequiel Bellorin-Font; Fergus J Caskey; Allan Collins; Alfonso M Cueto-Manzano; John Feehally; Bak Leong Goh; Kitty J Jager; Masaomi Nangaku; Muhibur Rahman; Manisha Sahay; Abdulkarim Saleh; Laura Sola; Rumeyza Turan Kazancioglu; Rachael C Walker; Robert Walker; Qiang Yao; Xueqing Yu; Ming-Hui Zhao; David W Johnson Journal: Kidney Int Suppl (2011) Date: 2020-02-19
Authors: Bruce M Robinson; Tadao Akizawa; Kitty J Jager; Peter G Kerr; Rajiv Saran; Ronald L Pisoni Journal: Lancet Date: 2016-05-22 Impact factor: 79.321