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Global, Regional, and National Burden of Chronic Kidney Disease, 1990–2017: A Systematic Analysis for the Global Burden of Disease Study 2017 Publisher Pubmed



Bikbov B1 ; Purcell C3 ; Levey AS4, 5 ; Smith M3 ; Abdoli A6 ; Abebe M7 ; Adebayo OM11 ; Afarideh M19 ; Agarwal SK23 ; Agudelobotero M24 ; Ahmadian E27, 30 ; Alaly Z31, 32 ; Alipour V35, 36 ; Almasihashiani A43 Show All Authors
Authors
  1. Bikbov B1
  2. Purcell C3
  3. Levey AS4, 5
  4. Smith M3
  5. Abdoli A6
  6. Abebe M7
  7. Adebayo OM11
  8. Afarideh M19
  9. Agarwal SK23
  10. Agudelobotero M24
  11. Ahmadian E27, 30
  12. Alaly Z31, 32
  13. Alipour V35, 36
  14. Almasihashiani A43
  15. Alraddadi RM40
  16. Alvisguzman N41, 42
  17. Amini S45
  18. Andrei T46
  19. Andrei CL47
  20. Andualem Z10
  21. Anjomshoa M49
  22. Arabloo J35
  23. Ashagre AF7
  24. Asmelash D7
  25. Ataro Z50
  26. Atout MMW51
  27. Ayanore MA52
  28. Badawi A53, 54
  29. Bakhtiari A20
  30. Ballew SH56
  31. Balouchi A39
  32. Banach M59, 60
  33. Barquera S62
  34. Basu S64
  35. Bayih MT67
  36. Bedi N69, 70
  37. Bello AK71
  38. Bensenor IM72
  39. Bijani A74
  40. Boloor A75
  41. Borzi AM76
  42. Camera LA77, 78
  43. Carrero JJ80
  44. Carvalho F86
  45. Castro F87
  46. Catalalopez F88, 89
  47. Chang AR90
  48. Chin KL91
  49. Chung SC93, 94
  50. Cirillo M95
  51. Cousin E96
  52. Dandona L3, 97
  53. Dandona R3, 97
  54. Daryani A99
  55. Das Gupta R100, 101
  56. Demeke FM66
  57. Demoz GT103, 104
  58. Desta DM107
  59. Do HP109
  60. Duncan BB96
  61. Eftekhari A25, 111
  62. Esteghamati A19
  63. Fatima SS112
  64. Fernandes JC113
  65. Fernandes E85
  66. Fischer F114
  67. Freitas M84
  68. Gad MM115, 116
  69. Gebremeskel GG102, 108
  70. Gebresillassie BM8
  71. Geta B118
  72. Ghafourifard M26
  73. Ghajar A19, 119
  74. Ghith N120, 121
  75. Gill PS122
  76. Ginawi IA123
  77. Gupta R124, 125
  78. Hafezinejad N22, 58
  79. Hajmirzaian A17, 129
  80. Hajmirzaian A17, 129
  81. Hariyani N131, 132
  82. Hasan M101
  83. Hasankhani M28
  84. Hasanzadeh A16, 110
  85. Hassen HY133, 134
  86. Hay SI2, 3
  87. Heidari B19
  88. Herteliu C46
  89. Hoang CL109
  90. Hosseini M14
  91. Hostiuc M48, 135
  92. Irvani SSN130
  93. Islam SMS136, 137
  94. Jafari Balalami N138
  95. James SL3
  96. Jassal SK33, 139
  97. Jha V141, 142
  98. Jonas JB143, 146
  99. Joukar F147
  100. Jozwiak JJ148
  101. Kabir A37
  102. Kahsay A106
  103. Kasaeian A21, 38
  104. Kassa TD105
  105. Kassaye HG149
  106. Khader YS151
  107. Khalilov R29
  108. Khan EA152
  109. Khan MS153
  110. Khang YH154
  111. Kisa A155
  112. Kovesdy CP156, 157
  113. Kuate Defo B158
  114. Kumar GA97
  115. Larsson AO159, 160
  116. Lim LL161, 162
  117. Lopez AD3, 163
  118. Lotufo PA73
  119. Majeed A63
  120. Malekzadeh R18, 164
  121. Marz W145, 165
  122. Masaka A166
  123. Meheretu HAA68, 167
  124. Miazgowski T168
  125. Mirica A46, 169
  126. Mirrakhimov EM170, 171
  127. Mithra P75
  128. Moazen B144, 172
  129. Mohammad DK81, 173
  130. Mohammadpourhodki R174
  131. Mohammed S145, 175
  132. Mokdad AH2, 3
  133. Morales L61
  134. Moreno Velasquez I87
  135. Mousavi SM15, 176
  136. Mukhopadhyay S177
  137. Nachega JB56, 178
  138. Nadkarni GN179
  139. Nansseu JR180, 181
  140. Natarajan G182
  141. Nazari J44, 183
  142. Neal B140, 184
  143. Negoi RI47, 185
  144. Nguyen CT186
  145. Nikbakhsh R17, 130
  146. Noubiap JJ187
  147. Nowak C83
  148. Olagunju AT188, 189
  149. Ortiz A190, 191
  150. Owolabi MO192
  151. Palladino R63, 193
  152. Pathak M194
  153. Perico N1
  154. Poustchi H18
  155. Prakash S195
  156. Prasad N195
  157. Rafiei A98
  158. Raju SB196
  159. Ramezanzadeh K127
  160. Rawaf S63, 197
  161. Rawaf DL65, 198
  162. Rawal L199
  163. Rezapour A35
  164. Ribeiro DC200
  165. Roever L201
  166. Rothenbacher D202
  167. Rwegerera GM203
  168. Saadatagah S13
  169. Safari S128
  170. Sahle BW204
  171. Salem H205
  172. Sanabria J206, 207
  173. Santos IS72
  174. Sarveazad A34
  175. Sawhney M208
  176. Schaeffner E209
  177. Schmidt MI96
  178. Schutte AE210, 211
  179. Sepanlou SG18, 164
  180. Shaikh MA212
  181. Sharafi Z213
  182. Sharif M214
  183. Sharifi A215
  184. Silva DAS216
  185. Singh JA217, 218
  186. Singh NP219
  187. Sisay MMM9, 220
  188. Soheili A222, 223
  189. Sutradhar I101
  190. Teklehaimanot BF150
  191. E Tesfay B150
  192. Teshome GF7
  193. Thakur JS224
  194. Tonelli M225
  195. Tran KB226, 227
  196. Tran BX228
  197. Tran Ngoc C229, 230
  198. Ullah I231, 232
  199. Valdez PR79, 233
  200. Varughese S234
  201. Vu LG109
  202. Waheed Y235
  203. Werdecker A236, 237
  204. Wolde HF9
  205. Wondmieneh AB104, 117
  206. Wulf Hanson S3
  207. Yamada T238
  208. Yeshaw Y9
  209. Yonemoto N239
  210. Yusefzadeh H221
  211. Zaidi Z240
  212. Zaki L241
  213. Zaman SB92, 242
  214. Zamora N243
  215. Zarghi A126
  216. Zewdie KA107
  217. Arnlov J12, 82
  218. Coresh J55
  219. Remuzzi G1
  220. Murray CJL2, 3
  221. Vos T2, 3

Source: The Lancet Published:2020


Abstract

Background: Health system planning requires careful assessment of chronic kidney disease (CKD) epidemiology, but data for morbidity and mortality of this disease are scarce or non-existent in many countries. We estimated the global, regional, and national burden of CKD, as well as the burden of cardiovascular disease and gout attributable to impaired kidney function, for the Global Burden of Diseases, Injuries, and Risk Factors Study 2017. We use the term CKD to refer to the morbidity and mortality that can be directly attributed to all stages of CKD, and we use the term impaired kidney function to refer to the additional risk of CKD from cardiovascular disease and gout. Methods: The main data sources we used were published literature, vital registration systems, end-stage kidney disease registries, and household surveys. Estimates of CKD burden were produced using a Cause of Death Ensemble model and a Bayesian meta-regression analytical tool, and included incidence, prevalence, years lived with disability, mortality, years of life lost, and disability-adjusted life-years (DALYs). A comparative risk assessment approach was used to estimate the proportion of cardiovascular diseases and gout burden attributable to impaired kidney function. Findings: Globally, in 2017, 1·2 million (95% uncertainty interval [UI] 1·2 to 1·3) people died from CKD. The global all-age mortality rate from CKD increased 41·5% (95% UI 35·2 to 46·5) between 1990 and 2017, although there was no significant change in the age-standardised mortality rate (2·8%, −1·5 to 6·3). In 2017, 697·5 million (95% UI 649·2 to 752·0) cases of all-stage CKD were recorded, for a global prevalence of 9·1% (8·5 to 9·8). The global all-age prevalence of CKD increased 29·3% (95% UI 26·4 to 32·6) since 1990, whereas the age-standardised prevalence remained stable (1·2%, −1·1 to 3·5). CKD resulted in 35·8 million (95% UI 33·7 to 38·0) DALYs in 2017, with diabetic nephropathy accounting for almost a third of DALYs. Most of the burden of CKD was concentrated in the three lowest quintiles of Socio-demographic Index (SDI). In several regions, particularly Oceania, sub-Saharan Africa, and Latin America, the burden of CKD was much higher than expected for the level of development, whereas the disease burden in western, eastern, and central sub-Saharan Africa, east Asia, south Asia, central and eastern Europe, Australasia, and western Europe was lower than expected. 1·4 million (95% UI 1·2 to 1·6) cardiovascular disease-related deaths and 25·3 million (22·2 to 28·9) cardiovascular disease DALYs were attributable to impaired kidney function. Interpretation: Kidney disease has a major effect on global health, both as a direct cause of global morbidity and mortality and as an important risk factor for cardiovascular disease. CKD is largely preventable and treatable and deserves greater attention in global health policy decision making, particularly in locations with low and middle SDI. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access Article under the CC BY 4.0 license.
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