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Estimates, Trends, and Drivers of the Global Burden of Type 2 Diabetes Attributable to Pm2·5 Air Pollution, 1990–2019: An Analysis of Data From the Global Burden of Disease Study 2019 Publisher Pubmed



Burkart K1, 2 ; Causey K4 ; Cohen AJ1, 5 ; Wozniak SS1 ; Salvi DD6 ; Abbafati C7 ; Adekanmbi V8 ; Adsuar JC9 ; Ahmadi K10 ; Alahdab F12 ; Alaly Z13, 14 ; Alipour V15, 16 ; Alvisguzman N20, 21 ; Amegah AK22 Show All Authors
Authors
  1. Burkart K1, 2
  2. Causey K4
  3. Cohen AJ1, 5
  4. Wozniak SS1
  5. Salvi DD6
  6. Abbafati C7
  7. Adekanmbi V8
  8. Adsuar JC9
  9. Ahmadi K10
  10. Alahdab F12
  11. Alaly Z13, 14
  12. Alipour V15, 16
  13. Alvisguzman N20, 21
  14. Amegah AK22
  15. Andrei CL23
  16. Andrei T25
  17. Ansari F26, 27
  18. Arabloo J15
  19. Aremu O28
  20. Aripov T29, 30
  21. Babaee E17
  22. Banach M31, 32
  23. Barnett A33
  24. Barnighausen TW34, 35
  25. Bedi N37, 38
  26. Behzadifar M39
  27. Bejot Y40, 41
  28. Bennett DA42
  29. Bensenor IM44
  30. Bernstein RS45, 46
  31. Bhattacharyya K47, 48
  32. Bijani A49
  33. Biondi A50
  34. Bohlouli S51
  35. Breitner S52, 53
  36. Brenner H54
  37. Butt ZA55, 56
  38. Camera LA57, 58
  39. Cantubrito C60
  40. Carvalho F61
  41. Cerin E33, 63
  42. Chattu VK64, 65
  43. Chauhan BG66, 68
  44. Choi JYJ69
  45. Chu DT70
  46. Dai X1, 2
  47. Dandona L1, 72, 73, 74
  48. Dandona R1, 72, 73
  49. Daryani A76
  50. Davletov K79
  51. De Courten B80
  52. Demeke FM83
  53. Denovagutierrez E84
  54. Dharmaratne SD2, 75, 85
  55. Dhimal M86
  56. Diaz D87, 88
  57. Djalalinia S89
  58. Duncan BB90
  59. El Sayed Zaki M91
  60. Eskandarieh S92
  61. Fareed M101
  62. Farzadfar F93
  63. Fattahi N282
  64. Fazlzadeh M94, 102
  65. Fernandes E62
  66. Filip I103, 104
  67. Fischer F105
  68. Foigt NA106
  69. Freitas M62
  70. Ghashghaee A107
  71. Gill PS108
  72. Ginawi IA109
  73. Gopalani SV110, 111
  74. Guo Y81, 112
  75. Gupta RD113, 114
  76. Habtewold TD115
  77. Hamadeh RR116
  78. Hamidi S117
  79. Hankey GJ118, 119
  80. Hasanpoor E120
  81. Hassen HY122, 123
  82. Hay SI1, 2
  83. Heibati B124
  84. Hole MK125
  85. Hossain N126
  86. Househ M127
  87. Irvani SSN128
  88. Jaafari J129
  89. Jakovljevic M130, 131
  90. Jha RP132, 133
  91. Jonas JB134, 135
  92. Jozwiak JJ136
  93. Kasaeian A18, 95
  94. Kaydi N137
  95. Khader YS139
  96. Khafaie MA138
  97. Khan EA140
  98. Khan J67
  99. Khan MN141
  100. Khatab K142, 143
  101. Khater AM144
  102. Kim YJ145
  103. Kimokoti RW146
  104. Kisa A147, 148
  105. Kivimaki M149, 150
  106. Knibbs LD151
  107. Kosen S152
  108. Koul PA153
  109. Koyanagi A154, 155
  110. Defo BK156, 157
  111. Kugbey N158
  112. Lauriola P159
  113. Lee PH160
  114. Leili M161
  115. Lewycka S43, 162
  116. Li S82
  117. Lim LL163, 164
  118. Linn S165
  119. Liu Y166, 167
  120. Lorkowski S168, 169
  121. Mahasha PW170
  122. Mahotra NB172
  123. Majeed A11
  124. Maleki A94, 173
  125. Malekzadeh R96, 174
  126. Mamun AA175
  127. Manafi N176
  128. Martini S177, 178
  129. Meharie BG179
  130. Menezes RG181
  131. Mestrovic T182, 183
  132. Miazgowski B184
  133. Miazgowski T185
  134. Miller TR186, 187
  135. Mini GK188, 189
  136. Mirica A25
  137. Mirrakhimov EM190, 191
  138. Mohajer B93
  139. Mohammed S192, 193
  140. Mohan V194, 195
  141. Mokdad AH1, 2
  142. Monasta L196
  143. Moraga P197
  144. Morrison SD3
  145. Mueller UO198, 199
  146. Mukhopadhyay S200
  147. Mustafa G201, 202
  148. Muthupandian S203, 204
  149. Naik G205
  150. Nangia V206
  151. Ndwandwe DE171
  152. Negoi RI24, 207
  153. Ningrum DNA208, 209
  154. Noubiap JJ210
  155. Ogbo FA212
  156. Olagunju AT213, 214
  157. Onwujekwe OE215
  158. Ortiz A216, 217
  159. Owolabi MO218, 219
  160. Mahesh PA220
  161. Pandajonas S221
  162. Park EK222
  163. Kan FP19
  164. Pirsaheb M282
  165. Postma MJ223, 224
  166. Pourjafar H121, 225
  167. Radfar A226
  168. Rafiei A77, 78
  169. Rahim F97
  170. Rahimimovaghar V98
  171. Rahman MA227, 228
  172. Rai RK229, 230
  173. Ranabhat CL231, 232
  174. Raoofi S233
  175. Rawal L234
  176. Renzaho AMN235, 236
  177. Rezapour A15
  178. Ribeiro D62, 237
  179. Roever L238
  180. Ronfani L196
  181. Sabour S239
  182. Saddik B240
  183. Sadeghi E282
  184. Moghaddam SS93
  185. Sahebkar A241, 242
  186. Sahraian MA92
  187. Salimzadeh H96
  188. Salvi SS243
  189. Samy AM244
  190. Sanabria J245, 246
  191. Sarmientosuarez R247, 248
  192. Sathish T283
  193. Schmidt MI90
  194. Schutte AE249, 250
  195. Sepanlou SG96, 174
  196. Shaikh MA251
  197. Sharafi K282
  198. Sheikh A36, 252
  199. Shigematsu M253
  200. Shiri R254
  201. Shirkoohi R99, 100
  202. Shuval K165, 255
  203. Soyiri IN256
  204. Tabaresseisdedos R257, 258
  205. Tefera YM180, 211
  206. Tehranibanihashemi A17, 19
  207. Temsah MH259
  208. Thankappan KR260
  209. Topormadry R261, 262
  210. Car LT263
  211. Ullah I264, 265
  212. Vacante M50
  213. Valdez PR59, 266
  214. Vasankari TJ267, 268
  215. Violante FS269, 270
  216. Waheed Y271
  217. Wolfe CDA272, 273
  218. Yamada T274
  219. Yonemoto N275, 276
  220. Yu C277
  221. Zaman SB80, 278
  222. Zhang Y279, 280
  223. Zodpey S71
  224. Lim SS1, 2
  225. Stanaway JD1, 2
  226. Brauer M1, 281

Source: The Lancet Planetary Health Published:2022


Abstract

Background: Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM2·5 originating from ambient and household air pollution. Methods: We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure–response curve from the extracted relative risk estimates using the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM2·5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals. Findings: In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68–4·83) deaths per 100 000 population and 167 (117–223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49–17·5) of deaths and 13·6% (9·73–17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22–9·53) of deaths and 5·92% (3·81–8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South America. Since 1990, the attributable burden has increased by 50%, driven largely by population growth and ageing. Globally, the impact of reductions in household air pollution was largely offset by increased ambient PM2·5. Interpretation: Air pollution is a major risk factor for diabetes. We estimated that about a fifth of the global burden of type 2 diabetes is attributable PM2·5 pollution. Air pollution mitigation therefore might have an essential role in reducing the global disease burden resulting from type 2 diabetes. Funding: Bill & Melinda Gates Foundation. © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license
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